Trajectory Prediction - LSTM - level1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    Author: Eswar Lakshminarayanan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datetime import datetime\n",
    "from random import sample\n",
    "import matplotlib.pyplot as plt \n",
    "from folium.plugins import HeatMap\n",
    "import folium\n",
    "import folium.plugins as plugins\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 1764258 #number of records in file\n",
    "s = 200000 #desired sample size\n",
    "skip = sorted(sample(range(1,n),n-s))\n",
    "df = pd.read_csv(\"new_level1_trajectory.csv\",header=0,skiprows=skip)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filter really short and long trajectories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.loc[(df.seq_len>10) & (df.seq_len<1500)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3409396, 5)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trajectory Length Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "df.seq_len.hist(bins =100)\n",
    "plt.xlabel(\"Length of Trajectory\",fontsize=26)\n",
    "plt.ylabel(\"Frequency\",fontsize=26)\n",
    "plt.title(\"Level 1\",fontsize=26)\n",
    "plt.xticks(np.arange(min(df.seq_len), max(df.seq_len)+1, 100),fontsize=20,rotation=70)\n",
    "plt.yticks(fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extract Lat Lon from Trajectories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "lat_lng =[]\n",
    "#lat_lng_time = []\n",
    "counter = 0\n",
    "counter2 = 0\n",
    "def fn(row):\n",
    "    l1 = []\n",
    "    l2 = []\n",
    "    for each_recording in eval(row[\"loc_info\"]):\n",
    "        _,lat,lng,time = each_recording\n",
    "        l1.append([lat,lng])\n",
    "        #l2.append([lat,lng,time])\n",
    "    lat_lng.append(l1)\n",
    "    #lat_lng_time.append(l2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[[\"loc_info\"]].apply(lambda x: fn(x),axis=1)\n",
    "df=None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3409396"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(lat_lng)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  train split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = []\n",
    "Y_train = []\n",
    "\n",
    "for each_traj in lat_lng[0:5000]:\n",
    "    X_train.append(each_traj[:len(each_traj)-1])\n",
    "    Y_train.append(each_traj[-1])\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Architectire"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/opc/anaconda3/envs/tf_keras/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "lstm_1 (LSTM)                (None, None, 256)         265216    \n",
      "_________________________________________________________________\n",
      "lstm_2 (LSTM)                (None, None, 128)         197120    \n",
      "_________________________________________________________________\n",
      "lstm_3 (LSTM)                (None, None, 64)          49408     \n",
      "_________________________________________________________________\n",
      "lstm_4 (LSTM)                (None, 32)                12416     \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 2)                 66        \n",
      "=================================================================\n",
      "Total params: 524,226\n",
      "Trainable params: 524,226\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout,TimeDistributed\n",
    "from keras.layers import Embedding\n",
    "from keras.layers import LSTM\n",
    "import numpy as np\n",
    "import keras.backend as K\n",
    "\n",
    "\n",
    "def euclidean_distance_loss(y_true, y_pred):\n",
    "    \"\"\"\n",
    "    Euclidean distance loss\n",
    "    :param y_true: TensorFlow/Theano tensor\n",
    "    :param y_pred: TensorFlow/Theano tensor of the same shape as y_true\n",
    "    :return: float\n",
    "    \"\"\"\n",
    "    euclidean_distance_loss.__name__ = \"Custom Loss\"\n",
    "    return K.sqrt(K.sum(K.square(y_pred - y_true), axis=-1))\n",
    "\n",
    "model = Sequential()\n",
    "model.add(LSTM(256, return_sequences=True,input_shape=(None, 2))) \n",
    "model.add(LSTM(128, return_sequences=True)) \n",
    "model.add(LSTM(64, return_sequences=True))\n",
    "model.add(LSTM(32))\n",
    "model.add(Dense(2))\n",
    "model.compile(loss=euclidean_distance_loss, optimizer='adam')\n",
    "model.summary()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Online Learning (Batch Size = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/opc/anaconda3/envs/tf_keras/lib/python3.7/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.cast instead.\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 103.8951\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 337ms/step - loss: 103.2041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 164ms/step - loss: 102.7448\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 102.4371\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 90ms/step - loss: 102.2191\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 102.0006\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 101.7963\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 324ms/step - loss: 101.5330\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 336ms/step - loss: 101.3254\n",
      "# 10 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 101.1351\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 169ms/step - loss: 100.9387\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 97ms/step - loss: 100.7644\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 100.6013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 179ms/step - loss: 100.4139\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 100.2531\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 100.0690\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 99.9277\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 99.7100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 99.5238\n",
      "# 20 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 859ms/step - loss: 99.3345\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 720ms/step - loss: 99.1597\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 368ms/step - loss: 98.9984\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 361ms/step - loss: 98.8411\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 98.6904\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 344ms/step - loss: 98.5640\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 98.4396\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 98.3208\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 441ms/step - loss: 98.2096\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 159ms/step - loss: 98.1157\n",
      "# 30 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 98.0245\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 97.9357\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 97.8509\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 97.7820\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 97.7177\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 666ms/step - loss: 97.6589\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 143ms/step - loss: 97.6111\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 97.5626\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 712ms/step - loss: 97.5154\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 827ms/step - loss: 97.4720\n",
      "# 40 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 97.4286\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 97.3867\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 259ms/step - loss: 97.3435\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 97.3001\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 97.2578\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 668ms/step - loss: 97.2160\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 307ms/step - loss: 97.1734\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 572ms/step - loss: 97.1303\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 243ms/step - loss: 97.0885\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 97.0482\n",
      "# 50 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 97.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 685ms/step - loss: 96.9682\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 96.9287\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 96.8891\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 96.8487\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 367ms/step - loss: 96.8100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 96.7713\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 318ms/step - loss: 96.7328\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 857ms/step - loss: 96.6947\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 96.6563\n",
      "# 60 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 96.6179\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 96.5797\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 96.5416\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 96.5030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 96.4657\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 251ms/step - loss: 96.4275\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 96.3894\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 96.3526\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 96.3152\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 96.2776\n",
      "# 70 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 451ms/step - loss: 96.2395\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 96.2031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 96.1661\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 96.1291\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 96.0922\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 96.0551\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 96.0185\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 95.9813\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 95.9442\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 95.9084\n",
      "# 80 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 371ms/step - loss: 95.8720\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 323ms/step - loss: 95.8357\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 401ms/step - loss: 95.7992\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 95.7626\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 176ms/step - loss: 95.7266\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 95.6907\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 95.6547\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 365ms/step - loss: 95.6175\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 370ms/step - loss: 95.5825\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 263ms/step - loss: 95.5465\n",
      "# 90 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 95.5101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 756ms/step - loss: 95.4745\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 95.4393\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 95.4029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 95.3673\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 95.3317\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 95.2968\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 95.2606\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 246ms/step - loss: 95.2258\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 95.1904\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# 100 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 818ms/step - loss: 95.1549\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 95.1199\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 95.0847\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 95.0493\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 95.0141\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 137ms/step - loss: 94.9790\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 94.9438\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 207ms/step - loss: 94.9081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 94.8738\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 94.8386\n",
      "# 110 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 113ms/step - loss: 94.8031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 696ms/step - loss: 94.7684\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 94.7328\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 94.6991\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 834ms/step - loss: 94.6633\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 94.6293\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 308ms/step - loss: 94.5943\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 313ms/step - loss: 94.5597\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 224ms/step - loss: 94.5252\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 94.4904\n",
      "# 120 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 94.4558\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 94.4200\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 94.3865\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 94.3520\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 94.3170\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 94.2828\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 94.2483\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 443ms/step - loss: 94.2137\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 94.1794\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 94.1447\n",
      "# 130 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 94.1096\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 918ms/step - loss: 94.0760\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 94.0408\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 416ms/step - loss: 94.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 93.9732\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 93.9384\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 194ms/step - loss: 93.9044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 639ms/step - loss: 93.8703\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 312ms/step - loss: 93.8360\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 93.8018\n",
      "# 140 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 93.7673\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 93.7334\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 93.6992\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 911ms/step - loss: 93.6650\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 93.6309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 93.5969\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 410ms/step - loss: 93.5619\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 93.5287\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 93.4941\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 93.4607\n",
      "# 150 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 93.4265\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 93.3922\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 346ms/step - loss: 93.3587\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 93.3242\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 604ms/step - loss: 93.2906\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 187ms/step - loss: 93.2562\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 93.2228\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 93.1888\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 93.1548\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 93.1210\n",
      "# 160 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 165ms/step - loss: 93.0873\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 93.0533\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 93.0195\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 92.9857\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 92.9515\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 92.9181\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 92.8842\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 143ms/step - loss: 92.8502\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 92.8165\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 92.7827\n",
      "# 170 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 92.7493\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 92.7152\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 92.6818\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 92.6471\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 92.6137\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 665ms/step - loss: 92.5807\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 92.5464\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 92.5134\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 92.4797\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 92.4451\n",
      "# 180 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 185ms/step - loss: 92.4125\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 92.3791\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 92.3453\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 92.3114\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 92.2781\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 189ms/step - loss: 92.2444\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 92.2109\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 92.1772\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 539ms/step - loss: 92.1428\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 92.1094\n",
      "# 190 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 893ms/step - loss: 92.0758\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 649ms/step - loss: 92.0423\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 534ms/step - loss: 92.0088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 91.9753\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 91.9418\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 91.9089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 592ms/step - loss: 91.8754\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 793ms/step - loss: 91.8424\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 91.8088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 91.7754\n",
      "# 200 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 161ms/step - loss: 91.7421\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 442ms/step - loss: 91.7086\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 91.6753\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 91.6419\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 97ms/step - loss: 91.6074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 254ms/step - loss: 91.5748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 91.5418\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 91.5083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 172ms/step - loss: 91.4745\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 91.4417\n",
      "# 210 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 91.4081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 336ms/step - loss: 91.3749\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 147ms/step - loss: 91.3407\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 445ms/step - loss: 91.3073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 91.2738\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 91.2417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 638ms/step - loss: 91.2080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 91.1751\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 91.1417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 91.1084\n",
      "# 220 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 91.0748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 182ms/step - loss: 91.0417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 276ms/step - loss: 91.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 90.9754\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 90.9419\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 478ms/step - loss: 90.9090\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 90.8758\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 90.8420\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 90.8092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 90.7757\n",
      "# 230 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 90.7428\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 116ms/step - loss: 90.7093\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 90.6763\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 90.6432\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 90.6098\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 120ms/step - loss: 90.5769\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 172ms/step - loss: 90.5438\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 552ms/step - loss: 90.5100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 90.4770\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 90.4441\n",
      "# 240 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 90.4100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 90.3779\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 90.3448\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 90.3112\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 928ms/step - loss: 90.2786\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 90.2454\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 535ms/step - loss: 90.2124\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 90.1791\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 90.1460\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 90.1124\n",
      "# 250 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 105ms/step - loss: 90.0796\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 90.0464\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 90.0139\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 89.9803\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 756ms/step - loss: 89.9465\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 750ms/step - loss: 89.9135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 430ms/step - loss: 89.8805\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 89.8485\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 647ms/step - loss: 89.8152\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 89.7820\n",
      "# 260 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 442ms/step - loss: 89.7493\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 89.7151\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 419ms/step - loss: 89.6821\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 89.6500\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 89.6161\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 89.5841\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 89.5511\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 89.5180\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 89.4849\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 89.4517\n",
      "# 270 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 89.4192\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 89.3852\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 89.3529\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 186ms/step - loss: 89.3201\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 89.2872\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 89.2542\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 89.2209\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 89.1874\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 89.1549\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 89.1216\n",
      "# 280 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 89.0892\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 89.0560\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 89.0235\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 88.9902\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 246ms/step - loss: 88.9564\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 88.9237\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 88.8907\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 88.8578\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 279ms/step - loss: 88.8250\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 88.7929\n",
      "# 290 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 88.7600\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 371ms/step - loss: 88.7269\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 88.6933\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 88.6614\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 88.6278\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 88.5947\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 88.5630\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 88.5298\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 88.4969\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 88.4629\n",
      "# 300 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 88.4312\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 88.3978\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 88.3650\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 768ms/step - loss: 88.3325\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 904ms/step - loss: 88.2986\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 88.2658\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 88.2333\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 88.2001\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 88.1682\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 88.1352\n",
      "# 310 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 352ms/step - loss: 88.1026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 88.0686\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 754ms/step - loss: 88.0358\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 88.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 851ms/step - loss: 87.9710\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 87.9373\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 87.9045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 87.8717\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 87.8389\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 87.8060\n",
      "# 320 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 87.7733\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 87.7404\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 776ms/step - loss: 87.7076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 373ms/step - loss: 87.6748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 896ms/step - loss: 87.6421\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 156ms/step - loss: 87.6093\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 221ms/step - loss: 87.5764\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 775ms/step - loss: 87.5437\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 87.5109\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 702ms/step - loss: 87.4780\n",
      "# 330 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 798ms/step - loss: 87.4453\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 87.4129\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 87.3798\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 781ms/step - loss: 87.3470\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 87.3142\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 87.2814\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 87.2488\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 590ms/step - loss: 87.2159\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 87.1833\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 87.1503\n",
      "# 340 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 87.1176\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 87.0856\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 87.0531\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 467ms/step - loss: 87.0194\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 86.9875\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 379ms/step - loss: 86.9540\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 493ms/step - loss: 86.9213\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 86.8885\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 86.8559\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 543ms/step - loss: 86.8230\n",
      "# 350 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 86.7904\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 86.7576\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 86.7250\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 86.6932\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 86.6595\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 86.6277\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 86.5951\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 86.5623\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 935ms/step - loss: 86.5290\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 86.4959\n",
      "# 360 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 482ms/step - loss: 86.4632\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 127ms/step - loss: 86.4305\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 369ms/step - loss: 86.3978\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 86.3651\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 86.3324\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 732ms/step - loss: 86.3004\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 86.2671\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 86.2343\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 86.2016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 86.1697\n",
      "# 370 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 86.1373\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 217ms/step - loss: 86.1048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 86.0721\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 344ms/step - loss: 86.0394\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 86.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 85.9741\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 85.9414\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 85.9088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 85.8761\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 85.8425\n",
      "# 380 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 214ms/step - loss: 85.8102\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 85.7770\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 778ms/step - loss: 85.7452\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 85.7118\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 85.6798\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 309ms/step - loss: 85.6465\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 85.6147\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 85.5812\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 300ms/step - loss: 85.5485\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 85.5159\n",
      "# 390 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 85.4833\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 85.4506\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 85.4180\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 85.3854\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 85.3528\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 85.3201\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 85.2886\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 85.2549\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 85.2223\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 542ms/step - loss: 85.1897\n",
      "# 400 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 85.1571\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 85.1245\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 85.0925\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 85.0593\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 413ms/step - loss: 85.0266\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 84.9949\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 84.9626\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 84.9287\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 376ms/step - loss: 84.8962\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 84.8636\n",
      "# 410 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 84.8309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 804ms/step - loss: 84.7984\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 84.7658\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 84.7332\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 84.7006\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 84.6681\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 961ms/step - loss: 84.6357\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 84.6037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 84.5703\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 84.5377\n",
      "# 420 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 84.5061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 84.4737\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 84.4410\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 84.4082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 84.3749\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 84.3423\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 282ms/step - loss: 84.3097\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 84.2772\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 84.2446\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 84.2120\n",
      "# 430 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 84.1795\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 483ms/step - loss: 84.1469\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 84.1144\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 84.0818\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 704ms/step - loss: 84.0502\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 84.0178\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 333ms/step - loss: 83.9853\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 292ms/step - loss: 83.9527\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 83.9202\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 397ms/step - loss: 83.8876\n",
      "# 440 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 983ms/step - loss: 83.8550\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 387ms/step - loss: 83.8225\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 83.7898\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 83.7575\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 519ms/step - loss: 83.7243\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 314ms/step - loss: 83.6918\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 295ms/step - loss: 83.6593\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 83.6267\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 485ms/step - loss: 83.5942\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 376ms/step - loss: 83.5617\n",
      "# 450 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 178ms/step - loss: 83.5291\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 83.4963\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 83.4636\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 230ms/step - loss: 83.4311\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 83.3988\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 83.3660\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 972ms/step - loss: 83.3344\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 143ms/step - loss: 83.3010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 959ms/step - loss: 83.2685\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 83.2360\n",
      "# 460 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 509ms/step - loss: 83.2035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 83.1714\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 83.1385\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 83.1058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 83.0734\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 83.0408\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 83.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.9765\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.9439\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.9115\n",
      "# 470 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.8789\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 82.8464\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 216ms/step - loss: 82.8142\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 762ms/step - loss: 82.7818\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 82.7493\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 82.7158\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 82.6833\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 82.6509\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 970ms/step - loss: 82.6184\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 369ms/step - loss: 82.5859\n",
      "# 480 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 399ms/step - loss: 82.5544\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 482ms/step - loss: 82.5220\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 82.4896\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.4569\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.4243\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 82.3920\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 82.3596\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 82.3272\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 82.2936\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 82.2610\n",
      "# 490 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 82.2286\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 82.1961\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 82.1637\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 946ms/step - loss: 82.1323\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.0998\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.0673\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 82.0347\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 82.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 81.9701\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 81.9364\n",
      "# 500 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 81.9039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 81.8714\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 81.8394\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 81.8069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 178ms/step - loss: 81.7745\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 81.7417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 81.7092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 81.6768\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 81.6443\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 81.6119\n",
      "# 510 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 81.5794\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 81.5475\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 3s 3s/step - loss: 81.5150\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 81.4827\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 81.4501\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 81.4177\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 81.3853\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 81.3529\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 123ms/step - loss: 81.3204\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 81.2880\n",
      "# 520 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 429ms/step - loss: 81.2557\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 81.2234\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 317ms/step - loss: 81.1912\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 81.1591\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 81.1252\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 81.0927\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 81.0603\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 230ms/step - loss: 81.0286\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 959ms/step - loss: 80.9961\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 80.9638\n",
      "# 530 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 926ms/step - loss: 80.9315\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 80.8991\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 393ms/step - loss: 80.8664\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 508ms/step - loss: 80.8343\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 932ms/step - loss: 80.8018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 173ms/step - loss: 80.7696\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 80.7371\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 80.7048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 80.6724\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 321ms/step - loss: 80.6399\n",
      "# 540 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 282ms/step - loss: 80.6075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 768ms/step - loss: 80.5750\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 756ms/step - loss: 80.5427\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 80.5102\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 139ms/step - loss: 80.4771\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 799ms/step - loss: 80.4453\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 80.4130\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 80.3806\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 80.3480\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 124ms/step - loss: 80.3159\n",
      "# 550 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 80.2828\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 80.2505\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 80.2180\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 80.1857\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 80.1532\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 80.1209\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 541ms/step - loss: 80.0886\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 80.0564\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 171ms/step - loss: 80.0241\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 160ms/step - loss: 79.9916\n",
      "# 560 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 79.9583\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 79.9259\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 329ms/step - loss: 79.8935\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 883ms/step - loss: 79.8612\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 323ms/step - loss: 79.8288\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 79.7964\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 79.7639\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 79.7316\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 516ms/step - loss: 79.6992\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 79.6674\n",
      "# 570 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 79.6352\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 79.6020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 79.5695\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 79.5376\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 623ms/step - loss: 79.5047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 79.4732\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 79.4411\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 646ms/step - loss: 79.4077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 79.3752\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 79.3431\n",
      "# 580 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 79.3113\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 79.2792\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 79.2466\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 79.2146\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 79.1819\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 79.1498\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 79.1174\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 79.0850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 79.0527\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 79.0206\n",
      "# 590 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 78.9879\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 78.9555\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 78.9230\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 246ms/step - loss: 78.8908\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 328ms/step - loss: 78.8575\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 78.8253\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 622ms/step - loss: 78.7930\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 78.7614\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 78.7287\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 78.6960\n",
      "# 600 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 78.6632\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 910ms/step - loss: 78.6308\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 552ms/step - loss: 78.5985\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 78.5666\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 428ms/step - loss: 78.5343\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 78.5019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 694ms/step - loss: 78.4690\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 166ms/step - loss: 78.4367\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 583ms/step - loss: 78.4044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 78.3720\n",
      "# 610 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 78.3396\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 78.3073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 78.2755\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 78.2432\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 225ms/step - loss: 78.2108\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 78.1783\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 78.1467\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 78.1142\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 78.0818\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 143ms/step - loss: 78.0495\n",
      "# 620 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 78.0172\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 77.9847\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 77.9523\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 360ms/step - loss: 77.9193\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 77.8879\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 77.8553\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 77.8232\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 253ms/step - loss: 77.7908\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 77.7582\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 77.7250\n",
      "# 630 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 77.6927\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 77.6608\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 77.6280\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 77.5957\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 77.5634\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 290ms/step - loss: 77.5310\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 77.4987\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 277ms/step - loss: 77.4664\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 317ms/step - loss: 77.4342\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 77.4018\n",
      "# 640 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 640ms/step - loss: 77.3693\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 889ms/step - loss: 77.3373\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 77.3056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 207ms/step - loss: 77.2734\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 77.2409\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 77.2085\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 814ms/step - loss: 77.1754\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 77.1436\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 77.1112\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 77.0789\n",
      "# 650 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 77.0466\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 77.0143\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 76.9819\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 76.9502\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 76.9179\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 526ms/step - loss: 76.8852\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 381ms/step - loss: 76.8529\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 76.8208\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 76.7877\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 76.7554\n",
      "# 660 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 76.7229\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 76.6909\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 181ms/step - loss: 76.6591\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 76.6259\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 76.5936\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 76.5613\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 76.5294\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 76.4976\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 349ms/step - loss: 76.4652\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 325ms/step - loss: 76.4321\n",
      "# 670 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 339ms/step - loss: 76.3997\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 76.3684\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 76.3358\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 76.3036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 76.2706\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 76.2392\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 76.2070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 76.1747\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 315ms/step - loss: 76.1424\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 76.1102\n",
      "# 680 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 76.0777\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 76.0455\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 76.0133\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 75.9808\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 75.9485\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 75.9163\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 75.8840\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 75.8517\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 75.8192\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.7869\n",
      "# 690 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 75.7536\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 75.7213\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 75.6891\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.6567\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.6245\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 522ms/step - loss: 75.5921\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.5600\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 75.5276\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 75.4954\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 75.4630\n",
      "# 700 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.4307\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 75.3984\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 835ms/step - loss: 75.3661\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 75.3344\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 75.3016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 361ms/step - loss: 75.2696\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 75.2373\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 75.2050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 75.1727\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 637ms/step - loss: 75.1404\n",
      "# 710 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.1082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.0759\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.0436\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 75.0113\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 74.9790\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 74.9474\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 74.9150\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 74.8825\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 88ms/step - loss: 74.8506\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.8173\n",
      "# 720 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.7850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.7527\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.7204\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 74.6882\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 74.6560\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 354ms/step - loss: 74.6235\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 428ms/step - loss: 74.5916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.5594\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.5267\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 74.4955\n",
      "# 730 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 74.4622\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 74.4298\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 618ms/step - loss: 74.3977\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.3654\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 211ms/step - loss: 74.3342\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 74.3018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 74.2696\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 74.2373\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 74.2051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 74.1726\n",
      "# 740 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 74.1405\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 74.1081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 883ms/step - loss: 74.0758\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 994ms/step - loss: 74.0437\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 74.0114\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 635ms/step - loss: 73.9791\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 961ms/step - loss: 73.9467\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 984ms/step - loss: 73.9146\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 73.8822\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 553ms/step - loss: 73.8501\n",
      "# 750 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 73.8178\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 73.7854\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 73.7533\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 73.7209\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 73.6886\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 73.6561\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 411ms/step - loss: 73.6239\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 73.5917\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 73.5593\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 720ms/step - loss: 73.5271\n",
      "# 760 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 73.4949\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 645ms/step - loss: 73.4626\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 73.4303\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 73.3983\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 73.3661\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 421ms/step - loss: 73.3328\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 73.3006\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 650ms/step - loss: 73.2696\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 73.2368\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 73.2050\n",
      "# 770 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 151ms/step - loss: 73.1726\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 666ms/step - loss: 73.1403\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 309ms/step - loss: 73.1081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 151ms/step - loss: 73.0748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 399ms/step - loss: 73.0436\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 73.0110\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 685ms/step - loss: 72.9787\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 898ms/step - loss: 72.9464\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 72.9138\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 72.8815\n",
      "# 780 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 72.8492\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 101ms/step - loss: 72.8169\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 72.7846\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 329ms/step - loss: 72.7524\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 305ms/step - loss: 72.7201\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 72.6890\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 72.6562\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 72.6239\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 72.5917\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 72.5594\n",
      "# 790 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 72.5272\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 72.4950\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 72.4627\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 338ms/step - loss: 72.4304\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 72.3986\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 72.3665\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 123ms/step - loss: 72.3338\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 72.3016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 72.2693\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 72.2371\n",
      "# 800 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 305ms/step - loss: 72.2043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 72.1718\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 72.1407\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 72.1082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 72.0762\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 72.0436\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 72.0114\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 71.9795\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 325ms/step - loss: 71.9469\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 71.9147\n",
      "# 810 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 71.8828\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 71.8506\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 71.8182\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 71.7860\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 71.7537\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 71.7218\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 71.6895\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 364ms/step - loss: 71.6571\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 786ms/step - loss: 71.6247\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 71.5923\n",
      "# 820 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 71.5605\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 71.5282\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 71.4958\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 857ms/step - loss: 71.4627\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 593ms/step - loss: 71.4311\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 713ms/step - loss: 71.3989\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 998ms/step - loss: 71.3667\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 743ms/step - loss: 71.3345\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 246ms/step - loss: 71.3022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 440ms/step - loss: 71.2700\n",
      "# 830 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 71.2377\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 71.2055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 71.1733\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 248ms/step - loss: 71.1415\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 71.1092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 240ms/step - loss: 71.0770\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 489ms/step - loss: 71.0443\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 71.0121\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 70.9799\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 70.9479\n",
      "# 840 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 70.9156\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 70.8838\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 70.8514\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 512ms/step - loss: 70.8193\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 513ms/step - loss: 70.7863\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 557ms/step - loss: 70.7545\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 401ms/step - loss: 70.7224\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 70.6903\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 70.6581\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 70.6259\n",
      "# 850 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 70.5937\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 70.5615\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 70.5290\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 70.4969\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 70.4643\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 70.4325\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 70.4003\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 70.3682\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 70.3348\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 273ms/step - loss: 70.3026\n",
      "# 860 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 337ms/step - loss: 70.2713\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 70.2392\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 70.2062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 70.1746\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 70.1425\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 70.1100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 70.0780\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 70.0456\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 329ms/step - loss: 70.0136\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 69.9806\n",
      "# 870 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 69.9485\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 489ms/step - loss: 69.9162\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 495ms/step - loss: 69.8844\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 69.8528\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 69.8199\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 69.7876\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 69.7555\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 69.7237\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 69.6907\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 69.6585\n",
      "# 880 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 69.6263\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 69.5940\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 69.5618\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 216ms/step - loss: 69.5296\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 69.4985\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 69.4661\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 46ms/step - loss: 69.4332\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 359ms/step - loss: 69.4012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 471ms/step - loss: 69.3690\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 241ms/step - loss: 69.3368\n",
      "# 890 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 286ms/step - loss: 69.3046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 69.2723\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 684ms/step - loss: 69.2401\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 69.2079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 69.1761\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 69.1440\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 69.1121\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 148ms/step - loss: 69.0798\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 69.0474\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 69.0154\n",
      "# 900 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 68.9822\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 68.9507\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 404ms/step - loss: 68.9178\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 68.8864\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 68.8543\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 68.8220\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 68.7889\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 68.7568\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 920ms/step - loss: 68.7249\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 436ms/step - loss: 68.6922\n",
      "# 910 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 341ms/step - loss: 68.6601\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 594ms/step - loss: 68.6279\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 68.5963\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 970ms/step - loss: 68.5641\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 68.5319\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 411ms/step - loss: 68.4997\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 68.4675\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 233ms/step - loss: 68.4357\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 68.4036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 68.3709\n",
      "# 920 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 68.3392\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 177ms/step - loss: 68.3068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 216ms/step - loss: 68.2746\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 68.2425\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 150ms/step - loss: 68.2103\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 68.1782\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 68.1460\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 68.1132\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 68.0814\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 68.0495\n",
      "# 930 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 68.0171\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 67.9850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 67.9527\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 917ms/step - loss: 67.9206\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 67.8886\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 67.8557\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 67.8234\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 880ms/step - loss: 67.7914\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 67.7600\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 67.7266\n",
      "# 940 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 415ms/step - loss: 67.6953\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 67.6632\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 67.6310\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 177ms/step - loss: 67.5989\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 674ms/step - loss: 67.5667\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 67.5346\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 67.5020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 67.4693\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 67.4376\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 67.4054\n",
      "# 950 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 67.3736\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 67.3412\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 67.3092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 228ms/step - loss: 67.2767\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 67.2445\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 919ms/step - loss: 67.2125\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 67.1802\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 67.1472\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 67.1150\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 67.0827\n",
      "# 960 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 67.0517\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 461ms/step - loss: 67.0185\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 66.9871\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 259ms/step - loss: 66.9548\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 66.9225\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 66.8907\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 66.8585\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 66.8263\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 66.7937\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 337ms/step - loss: 66.7613\n",
      "# 970 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 233ms/step - loss: 66.7292\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 556ms/step - loss: 66.6968\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 66.6645\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 66.6323\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 108ms/step - loss: 66.6001\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 761ms/step - loss: 66.5680\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 105ms/step - loss: 66.5359\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 457ms/step - loss: 66.5036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 66.4714\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 66.4392\n",
      "# 980 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 66.4071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 66.3749\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 66.3427\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 993ms/step - loss: 66.3105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 66.2784\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 66.2462\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 66.2139\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 66.1817\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 66.1496\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 66.1176\n",
      "# 990 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 66.0852\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 66.0531\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 580ms/step - loss: 66.0210\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 216ms/step - loss: 65.9888\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 777ms/step - loss: 65.9577\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 462ms/step - loss: 65.9245\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 65.8930\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 65.8602\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 280ms/step - loss: 65.8287\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 219ms/step - loss: 65.7959\n",
      "# 1000 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 65.7636\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 65.7314\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 65.6992\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 280ms/step - loss: 65.6671\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 392ms/step - loss: 65.6349\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 65.6028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 65.5706\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 564ms/step - loss: 65.5384\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 242ms/step - loss: 65.5062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 65.4740\n",
      "# 1010 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 65.4419\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 65.4097\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 65.3776\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 65.3454\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 367ms/step - loss: 65.3131\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 232ms/step - loss: 65.2810\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 235ms/step - loss: 65.2489\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 65.2167\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 65.1845\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 279ms/step - loss: 65.1535\n",
      "# 1020 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 65.1202\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 65.0881\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 65.0559\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 65.0238\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 64.9916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 64.9594\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 64.9272\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 153ms/step - loss: 64.8952\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 64.8636\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 173ms/step - loss: 64.8309\n",
      "# 1030 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 291ms/step - loss: 64.7986\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 64.7670\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 379ms/step - loss: 64.7352\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 64.7021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 64.6699\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 597ms/step - loss: 64.6377\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 64.6055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 64.5734\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 238ms/step - loss: 64.5412\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 64.5091\n",
      "# 1040 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 64.4768\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 703ms/step - loss: 64.4447\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 361ms/step - loss: 64.4125\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 185ms/step - loss: 64.3804\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 379ms/step - loss: 64.3482\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 64.3161\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 494ms/step - loss: 64.2850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 385ms/step - loss: 64.2518\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 64.2197\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 456ms/step - loss: 64.1882\n",
      "# 1050 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 702ms/step - loss: 64.1562\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 64.1242\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 389ms/step - loss: 64.0910\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 64.0588\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 64.0267\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 63.9946\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 63.9624\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 63.9310\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 936ms/step - loss: 63.8990\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 63.8670\n",
      "# 1060 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 63.8338\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 168ms/step - loss: 63.8016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 737ms/step - loss: 63.7695\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 63.7374\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 409ms/step - loss: 63.7051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 934ms/step - loss: 63.6729\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 63.6409\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 329ms/step - loss: 63.6087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 464ms/step - loss: 63.5766\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 63.5444\n",
      "# 1070 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 63.5122\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 63.4801\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 63.4480\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 63.4159\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 63.3836\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 63.3522\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 182ms/step - loss: 63.3201\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 63.2877\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 63.2560\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 63.2240\n",
      "# 1080 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 63.1916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 63.1597\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 63.1275\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 224ms/step - loss: 63.0953\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 63.0629\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 63.0307\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 709ms/step - loss: 62.9989\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 62.9660\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 62.9344\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 62.9018\n",
      "# 1090 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 146ms/step - loss: 62.8703\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 62.8381\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 62.8061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 62.7739\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 62.7416\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 62.7095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 62.6775\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 287ms/step - loss: 62.6453\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 410ms/step - loss: 62.6131\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 348ms/step - loss: 62.5810\n",
      "# 1100 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 62.5489\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 62.5167\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 62.4845\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 62.4525\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 62.4203\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 62.3880\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 62.3561\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 62.3238\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 62.2915\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 62.2592\n",
      "# 1110 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 62.2271\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 62.1949\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 62.1627\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 62.1308\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 648ms/step - loss: 62.0978\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 62.0663\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 296ms/step - loss: 62.0335\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 498ms/step - loss: 62.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 61.9699\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 61.9370\n",
      "# 1120 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 61.9049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 61.8738\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 61.8416\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 61.8096\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 61.7774\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 61.7452\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 753ms/step - loss: 61.7132\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 61.6810\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 714ms/step - loss: 61.6477\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 61.6156\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# 1130 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 61.5845\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 345ms/step - loss: 61.5513\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 61.5192\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 61.4870\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 61.4549\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 61.4228\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 256ms/step - loss: 61.3906\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 61.3584\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 61.3263\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 61.2941\n",
      "# 1140 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 61.2626\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 61.2305\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 347ms/step - loss: 61.1977\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 413ms/step - loss: 61.1656\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 61.1335\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 61.1023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 61.0693\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 61.0381\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 336ms/step - loss: 61.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 60.9738\n",
      "# 1150 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 475ms/step - loss: 60.9407\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 60.9086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 60.8775\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 402ms/step - loss: 60.8442\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 60.8122\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 190ms/step - loss: 60.7801\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 60.7479\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 296ms/step - loss: 60.7157\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 60.6845\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 940ms/step - loss: 60.6520\n",
      "# 1160 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 60.6194\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 60.5881\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 60.5562\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 60.5239\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 60.4908\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 363ms/step - loss: 60.4588\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 60.4267\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 60.3945\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 60.3632\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 60.3313\n",
      "# 1170 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 839ms/step - loss: 60.2985\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 195ms/step - loss: 60.2659\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 60.2338\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 60.2022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 60.1706\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 60.1375\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 361ms/step - loss: 60.1060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 60.0741\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 60.0421\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 60.0097\n",
      "# 1180 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 59.9770\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 59.9446\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 59.9124\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 59.8803\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 59.8482\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 385ms/step - loss: 59.8160\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 59.7839\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 254ms/step - loss: 59.7517\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 59.7196\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 813ms/step - loss: 59.6875\n",
      "# 1190 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 59.6553\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 59.6233\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 59.5914\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 393ms/step - loss: 59.5601\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 59.5280\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 59.4958\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 59.4630\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 59.4315\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 59.3994\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 59.3672\n",
      "# 1200 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 59.3350\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 59.3025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 59.2708\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 59.2389\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 59.2067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 187ms/step - loss: 59.1735\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 59.1421\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 550ms/step - loss: 59.1099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 59.0778\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 59.0457\n",
      "# 1210 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 299ms/step - loss: 59.0128\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 58.9807\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 58.9488\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 381ms/step - loss: 58.9164\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 58.8843\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 58.8522\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 239ms/step - loss: 58.8201\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 58.7879\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 58.7562\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 58.7237\n",
      "# 1220 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 167ms/step - loss: 58.6916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 244ms/step - loss: 58.6595\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 809ms/step - loss: 58.6274\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 371ms/step - loss: 58.5960\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 58.5631\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 58.5309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 58.4989\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 58.4668\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 58.4346\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 58.4025\n",
      "# 1230 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 277ms/step - loss: 58.3704\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 58.3382\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 58.3072\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 58.2752\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 659ms/step - loss: 58.2430\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 58.2108\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 58.1788\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 58.1464\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 58.1146\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 58.0821\n",
      "# 1240 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 58.0504\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 58.0180\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 57.9859\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 57.9538\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 57.9216\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 57.8897\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 57.8577\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 57.8253\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 57.7932\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 57.7611\n",
      "# 1250 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 57.7289\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 57.6969\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 641ms/step - loss: 57.6648\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 57.6316\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 57.6000\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 57.5685\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 57.5365\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 57.5044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 57.4722\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 57.4399\n",
      "# 1260 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 57.4078\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 57.3757\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 57.3436\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 97ms/step - loss: 57.3116\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 57.2795\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 57.2473\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 57.2153\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 57.1830\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 57.1511\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 57.1190\n",
      "# 1270 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 57.0869\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 323ms/step - loss: 57.0545\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 57.0226\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 116ms/step - loss: 56.9898\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 56.9581\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 827ms/step - loss: 56.9257\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 56.8935\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 56.8618\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 56.8298\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 622ms/step - loss: 56.7978\n",
      "# 1280 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 56.7651\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 56.7336\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 407ms/step - loss: 56.7015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 56.6694\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 56.6373\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 56.6052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 56.5730\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 56.5410\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 258ms/step - loss: 56.5085\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 404ms/step - loss: 56.4767\n",
      "# 1290 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 56.4435\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 56.4121\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 56.3804\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 269ms/step - loss: 56.3478\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 56.3151\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 56.2828\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 56.2508\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 56.2186\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 56.1866\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 56.1545\n",
      "# 1300 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 56.1223\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 56.0902\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 56.0581\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 56.0260\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 55.9939\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 55.9618\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 55.9301\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 55.8976\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 55.8655\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 55.8344\n",
      "# 1310 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 55.8013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 55.7693\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 549ms/step - loss: 55.7370\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 55.7049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 55.6728\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 55.6412\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 55.6086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 202ms/step - loss: 55.5775\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 55.5446\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 55.5133\n",
      "# 1320 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 226ms/step - loss: 55.4812\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 55.4491\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 55.4170\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 902ms/step - loss: 55.3837\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 55.3528\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 55.3205\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 55.2884\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 55.2559\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 55.2243\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 55.1920\n",
      "# 1330 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 55.1600\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 55.1279\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 55.0955\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 172ms/step - loss: 55.0639\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 55.0309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 54.9993\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 54.9675\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 54.9353\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 54.9032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 567ms/step - loss: 54.8701\n",
      "# 1340 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 54.8381\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 54.8060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 54.7745\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 230ms/step - loss: 54.7417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 489ms/step - loss: 54.7096\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 54.6775\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 293ms/step - loss: 54.6454\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 147ms/step - loss: 54.6133\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 245ms/step - loss: 54.5812\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 148ms/step - loss: 54.5491\n",
      "# 1350 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 54.5170\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 570ms/step - loss: 54.4856\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 54.4537\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 54.4209\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 54.3886\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 522ms/step - loss: 54.3564\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 54.3250\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 101ms/step - loss: 54.2934\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 683ms/step - loss: 54.2613\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 292ms/step - loss: 54.2291\n",
      "# 1360 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 257ms/step - loss: 54.1967\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 191ms/step - loss: 54.1649\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 54.1327\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 54.1010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 54.0688\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 54.0365\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 54.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 53.9722\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 53.9401\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 53.9082\n",
      "# 1370 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 53.8760\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 53.8438\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 53.8110\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 53.7793\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 737ms/step - loss: 53.7466\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 347ms/step - loss: 53.7146\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 221ms/step - loss: 53.6824\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 260ms/step - loss: 53.6514\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 53.6194\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 53.5872\n",
      "# 1380 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 194ms/step - loss: 53.5551\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 567ms/step - loss: 53.5229\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 176ms/step - loss: 53.4898\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 795ms/step - loss: 53.4587\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 609ms/step - loss: 53.4267\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 597ms/step - loss: 53.3936\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 191ms/step - loss: 53.3614\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 53.3294\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 160ms/step - loss: 53.2973\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 476ms/step - loss: 53.2651\n",
      "# 1390 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 53.2336\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 53.2010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 53.1689\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 53.1367\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 200ms/step - loss: 53.1046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 396ms/step - loss: 53.0734\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 195ms/step - loss: 53.0403\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 163ms/step - loss: 53.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 52.9763\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.9441\n",
      "# 1400 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 399ms/step - loss: 52.9121\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.8799\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 997ms/step - loss: 52.8480\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 389ms/step - loss: 52.8157\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 52.7838\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 372ms/step - loss: 52.7516\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.7205\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 52.6885\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 905ms/step - loss: 52.6555\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.6242\n",
      "# 1410 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 52.5921\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 52.5602\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 52.5281\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 198ms/step - loss: 52.4959\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 438ms/step - loss: 52.4636\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.4317\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 52.3994\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 52.3673\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 52.3355\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 52.3035\n",
      "# 1420 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 913ms/step - loss: 52.2713\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 52.2392\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.2069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.1739\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.1418\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 464ms/step - loss: 52.1099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 52.0777\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 52.0465\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 52.0142\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 51.9821\n",
      "# 1430 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 51.9499\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 51.9178\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 398ms/step - loss: 51.8859\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 51.8541\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 51.8218\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 51.7892\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 51.7575\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 51.7256\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 516ms/step - loss: 51.6935\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 51.6613\n",
      "# 1440 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 51.6285\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 51.5972\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 51.5653\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 942ms/step - loss: 51.5330\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 51.5005\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 51.4687\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 51.4367\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 51.4046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 51.3719\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 51.3402\n",
      "# 1450 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 51.3086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 51.2764\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 51.2443\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 260ms/step - loss: 51.2123\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 147ms/step - loss: 51.1802\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 51.1477\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 51.1160\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 51.0828\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 812ms/step - loss: 51.0507\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 51.0193\n",
      "# 1460 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 50.9871\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 50.9556\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 581ms/step - loss: 50.9229\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 168ms/step - loss: 50.8911\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 273ms/step - loss: 50.8593\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 50.8272\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 50.7952\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 50.7630\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 433ms/step - loss: 50.7310\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 50.6989\n",
      "# 1470 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 50.6668\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 50.6347\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 50.6026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 50.5706\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 50.5378\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 50.5057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 385ms/step - loss: 50.4741\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 50.4422\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 50.4098\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 50.3777\n",
      "# 1480 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 50.3456\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 50.3136\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 50.2817\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 50.2497\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 50.2173\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 50.1852\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 50.1531\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 112ms/step - loss: 50.1210\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 50.0891\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 50.0568\n",
      "# 1490 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 50.0247\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 49.9927\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 49.9606\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 49.9285\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 49.8964\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 49.8644\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 49.8323\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 49.8004\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 49.7682\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 49.7360\n",
      "# 1500 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 49.7039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 49.6718\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 49.6396\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 49.6076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 49.5755\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 150ms/step - loss: 49.5437\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 49.5114\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 49.4794\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 386ms/step - loss: 49.4476\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 340ms/step - loss: 49.4151\n",
      "# 1510 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 49.3833\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 49.3509\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 49.3192\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 49.2872\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 49.2550\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 49.2229\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 49.1908\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 323ms/step - loss: 49.1587\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 49.1267\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 49.0947\n",
      "# 1520 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 49.0615\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 49.0293\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 48.9984\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 48.9659\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 48.9341\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 432ms/step - loss: 48.9013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 48.8698\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 309ms/step - loss: 48.8369\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 898ms/step - loss: 48.8050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 48.7738\n",
      "# 1530 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 48.7415\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 48.7086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 48.6774\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 48.6455\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 274ms/step - loss: 48.6135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 247ms/step - loss: 48.5802\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 451ms/step - loss: 48.5482\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 419ms/step - loss: 48.5160\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 264ms/step - loss: 48.4842\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 48.4521\n",
      "# 1540 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 254ms/step - loss: 48.4200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 291ms/step - loss: 48.3878\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 444ms/step - loss: 48.3557\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 207ms/step - loss: 48.3235\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 411ms/step - loss: 48.2916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 337ms/step - loss: 48.2596\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 48.2273\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 146ms/step - loss: 48.1955\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 48.1634\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 747ms/step - loss: 48.1322\n",
      "# 1550 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 48.0995\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 48.0675\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 48.0354\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 48.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 192ms/step - loss: 47.9710\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 47.9391\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 47.9070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 972ms/step - loss: 47.8756\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 302ms/step - loss: 47.8435\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 670ms/step - loss: 47.8109\n",
      "# 1560 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 47.7789\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 47.7469\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 47.7147\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 47.6826\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 47.6505\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 47.6188\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 47.5869\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 47.5547\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 47.5225\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 47.4908\n",
      "# 1570 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 553ms/step - loss: 47.4582\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 47.4262\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 404ms/step - loss: 47.3943\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 452ms/step - loss: 47.3619\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 148ms/step - loss: 47.3298\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 47.2978\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 47.2657\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 47.2338\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 47.2019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 47.1697\n",
      "# 1580 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 47.1378\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 675ms/step - loss: 47.1056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 47.0737\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 47.0416\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 843ms/step - loss: 47.0095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 46.9775\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 46.9454\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 46.9123\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 356ms/step - loss: 46.8801\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 46.8481\n",
      "# 1590 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 46.8160\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 886ms/step - loss: 46.7838\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 46.7518\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 46.7197\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 46.6877\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 46.6556\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 544ms/step - loss: 46.6235\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 46.5914\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 46.5594\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 910ms/step - loss: 46.5273\n",
      "# 1600 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 46.4953\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 46.4638\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 851ms/step - loss: 46.4311\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 46.3990\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 46.3669\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 46.3348\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 46.3036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 657ms/step - loss: 46.2719\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 46.2391\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 46.2075\n",
      "# 1610 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 419ms/step - loss: 46.1744\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 46.1425\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 384ms/step - loss: 46.1104\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 658ms/step - loss: 46.0782\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 46.0472\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 46.0141\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 652ms/step - loss: 45.9821\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 45.9509\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 45.9190\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 45.8868\n",
      "# 1620 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 547ms/step - loss: 45.8548\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 497ms/step - loss: 45.8216\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 45.7905\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 655ms/step - loss: 45.7580\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 305ms/step - loss: 45.7256\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 329ms/step - loss: 45.6934\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 814ms/step - loss: 45.6621\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 45.6292\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 45.5979\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 45.5661\n",
      "# 1630 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 45.5341\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 45.5020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 45.4691\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 45.4374\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 201ms/step - loss: 45.4057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 45.3734\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 45.3418\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 45.3099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 45.2773\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 45.2457\n",
      "# 1640 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 45.2130\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 45.1813\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 45.1491\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 1s 544ms/step - loss: 45.1164\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 45.0843\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 45.0520\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 150ms/step - loss: 45.0203\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 44.9882\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 44.9559\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 778ms/step - loss: 44.9237\n",
      "# 1650 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 44.8926\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 44.8606\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 44.8275\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 44.7954\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 44.7643\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 44.7314\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 44.7001\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 279ms/step - loss: 44.6683\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 44.6362\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 44.6034\n",
      "# 1660 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 44.5714\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 44.5394\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 576ms/step - loss: 44.5077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 44.4747\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 912ms/step - loss: 44.4426\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 568ms/step - loss: 44.4117\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 506ms/step - loss: 44.3796\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 44.3465\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 44.3156\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 572ms/step - loss: 44.2827\n",
      "# 1670 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 850ms/step - loss: 44.2512\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 590ms/step - loss: 44.2192\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 44.1861\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 675ms/step - loss: 44.1541\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 602ms/step - loss: 44.1219\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 692ms/step - loss: 44.0899\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 44.0588\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 44.0258\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 43.9948\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 43.9620\n",
      "# 1680 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 43.9307\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 43.8983\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 43.8659\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 528ms/step - loss: 43.8339\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 293ms/step - loss: 43.8025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 43.7698\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 43.7377\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 524ms/step - loss: 43.7060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 43.6739\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 237ms/step - loss: 43.6421\n",
      "# 1690 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 796ms/step - loss: 43.6095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 43.5778\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 43.5455\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 43.5135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 149ms/step - loss: 43.4813\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 43.4497\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 123ms/step - loss: 43.4177\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 43.3849\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 43.3529\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 105ms/step - loss: 43.3208\n",
      "# 1700 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 43.2888\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 426ms/step - loss: 43.2569\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 675ms/step - loss: 43.2250\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 330ms/step - loss: 43.1926\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 43.1612\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 43.1287\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 202ms/step - loss: 43.0968\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 43.0643\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 43.0324\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 43.0001\n",
      "# 1710 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 42.9681\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 42.9359\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 42.9040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 42.8720\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 42.8399\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 490ms/step - loss: 42.8080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 42.7763\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 963ms/step - loss: 42.7441\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 42.7123\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 42.6802\n",
      "# 1720 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 42.6481\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 42.6161\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 42.5840\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 42.5520\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 42.5199\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 42.4878\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 42.4557\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 42.4237\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 42.3916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 42.3596\n",
      "# 1730 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 42.3276\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 42.2954\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 42.2634\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 42.2309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 42.1992\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 42.1672\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 42.1351\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 42.1031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 42.0707\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 141ms/step - loss: 42.0390\n",
      "# 1740 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 42.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 41.9748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 41.9428\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 41.9107\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 242ms/step - loss: 41.8787\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 41.8466\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 41.8145\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 41.7824\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 41.7503\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 182ms/step - loss: 41.7179\n",
      "# 1750 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 365ms/step - loss: 41.6858\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 41.6538\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 41.6219\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 41.5895\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 41.5573\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 846ms/step - loss: 41.5258\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 41.4931\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 41.4617\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 41.4297\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 147ms/step - loss: 41.3974\n",
      "# 1760 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 41.3653\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 41.3333\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 145ms/step - loss: 41.3010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 41.2689\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 41.2367\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 41.2041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 41.1721\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 41.1402\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 252ms/step - loss: 41.1088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 41.0768\n",
      "# 1770 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 291ms/step - loss: 41.0449\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 556ms/step - loss: 41.0127\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 40.9807\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 40.9487\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 262ms/step - loss: 40.9164\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 427ms/step - loss: 40.8847\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 40.8526\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 40.8203\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 40.7883\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 40.7563\n",
      "# 1780 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 40.7244\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 40.6920\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 40.6600\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 40.6278\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 199ms/step - loss: 40.5962\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 40.5639\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 40.5318\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 40.4998\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 40.4677\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 40.4348\n",
      "# 1790 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 247ms/step - loss: 40.4035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 40.3715\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 40.3395\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 144ms/step - loss: 40.3072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 40.2750\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 40.2435\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 40.2111\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 40.1790\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 40.1471\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 40.1150\n",
      "# 1800 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 40.0829\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 40.0509\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 197ms/step - loss: 40.0187\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 39.9870\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 39.9547\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 39.9228\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 39.8907\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 39.8588\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 39.8268\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 39.7944\n",
      "# 1810 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 39.7624\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 39.7303\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 39.6983\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 39.6664\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 39.6344\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 515ms/step - loss: 39.6021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 470ms/step - loss: 39.5702\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 39.5383\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 39.5053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 39.4739\n",
      "# 1820 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 528ms/step - loss: 39.4410\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 39.4101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 39.3776\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 39.3456\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 39.3133\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 39.2819\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 39.2497\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 39.2170\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 39.1850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 39.1530\n",
      "# 1830 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 39.1210\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 39.0889\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 39.0568\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 39.0247\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 157ms/step - loss: 38.9929\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 94ms/step - loss: 38.9610\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 38.9289\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 38.8969\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 38.8641\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 38.8326\n",
      "# 1840 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 38.8003\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 38.7690\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 38.7366\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 38.7045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 38.6724\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 38.6404\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 38.6084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 38.5763\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 38.5443\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 38.5121\n",
      "# 1850 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 38.4804\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 38.4477\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 38.4164\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 260ms/step - loss: 38.3830\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 38.3515\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 38.3197\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 220ms/step - loss: 38.2879\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 38.2559\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 270ms/step - loss: 38.2240\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 38.1920\n",
      "# 1860 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 38.1598\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 38.1277\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 38.0956\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 38.0638\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 38.0315\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 349ms/step - loss: 37.9994\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 293ms/step - loss: 37.9668\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 37.9347\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 37.9027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 37.8712\n",
      "# 1870 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 37.8391\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 37.8072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 37.7742\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 37.7433\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 37.7107\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 217ms/step - loss: 37.6791\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 558ms/step - loss: 37.6469\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 37.6149\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 37.5828\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 37.5507\n",
      "# 1880 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 37.5189\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 836ms/step - loss: 37.4868\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 515ms/step - loss: 37.4548\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 37.4225\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 37.3905\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 37.3586\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 37.3263\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 143ms/step - loss: 37.2938\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 37.2616\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 701ms/step - loss: 37.2301\n",
      "# 1890 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 225ms/step - loss: 37.1975\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 37.1660\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 37.1340\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 37.1013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 105ms/step - loss: 37.0695\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 37.0380\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 250ms/step - loss: 37.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 36.9733\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 36.9417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 36.9099\n",
      "# 1900 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 36.8777\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 36.8445\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 36.8135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 156ms/step - loss: 36.7816\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 469ms/step - loss: 36.7494\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 809ms/step - loss: 36.7174\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 36.6854\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 36.6533\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 592ms/step - loss: 36.6212\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 36.5891\n",
      "# 1910 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 36.5571\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 36.5250\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 311ms/step - loss: 36.4930\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 36.4612\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 36.4288\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 36.3972\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 36.3646\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 173ms/step - loss: 36.3327\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 690ms/step - loss: 36.3009\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 36.2684\n",
      "# 1920 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 36.2365\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 36.2045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 36.1724\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 36.1403\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 36.1083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 36.0762\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 36.0441\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 36.0121\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 35.9801\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 35.9481\n",
      "# 1930 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 136ms/step - loss: 35.9161\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 35.8843\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 35.8520\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 35.8199\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 35.7880\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 35.7558\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 35.7240\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 35.6916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 35.6597\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 35.6276\n",
      "# 1940 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 623ms/step - loss: 35.5954\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 35.5635\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 35.5314\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 35.4990\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 35.4674\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 35.4353\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 35.4034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 35.3712\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 35.3390\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 35.3071\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# 1950 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 35.2750\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 35.2430\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 35.2109\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 35.1789\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 35.1468\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 35.1148\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 35.0830\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 35.0508\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 35.0185\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 34.9869\n",
      "# 1960 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 34.9549\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 34.9228\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 34.8904\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 34.8583\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 34.8265\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 34.7940\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 34.7619\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 34.7299\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 34.6978\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 245ms/step - loss: 34.6652\n",
      "# 1970 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 34.6342\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 34.6017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 113ms/step - loss: 34.5697\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 206ms/step - loss: 34.5381\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 34.5061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 34.4741\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 34.4421\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 34.4100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 34.3779\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 34.3459\n",
      "# 1980 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 137ms/step - loss: 34.3139\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 34.2818\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 34.2498\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 159ms/step - loss: 34.2168\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 108ms/step - loss: 34.1849\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 34.1528\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 34.1209\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 34.0888\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 34.0574\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 34.0254\n",
      "# 1990 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 33.9935\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 33.9612\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 33.9292\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 33.8970\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 33.8652\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 33.8333\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 33.8012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 33.7684\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 33.7371\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 33.7050\n",
      "# 2000 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 33.6729\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 33.6409\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 33.6088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 33.5762\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 33.5442\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 33.5121\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 33.4804\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 171ms/step - loss: 33.4485\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 33.4163\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 33.3845\n",
      "# 2010 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 33.3521\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 33.3202\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 33.2883\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 33.2560\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 33.2241\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 33.1920\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 33.1599\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 33.1279\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 33.0960\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 33.0638\n",
      "# 2020 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 33.0318\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 32.9997\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 32.9677\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 32.9359\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 32.9036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 32.8718\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 32.8395\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 32.8074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 32.7756\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 32.7433\n",
      "# 2030 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 32.7114\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 32.6795\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 32.6475\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 32.6155\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 32.5835\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 32.5514\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 32.5194\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 208ms/step - loss: 32.4874\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 32.4552\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 32.4232\n",
      "# 2040 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 32.3912\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 146ms/step - loss: 32.3592\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 32.3271\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 32.2951\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 32.2627\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 32.2307\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 32.1985\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 32.1667\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 32.1349\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 32.1028\n",
      "# 2050 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 32.0708\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 32.0387\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 291ms/step - loss: 32.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 31.9747\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 31.9426\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 31.9106\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 31.8785\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 31.8465\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 31.8144\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 31.7824\n",
      "# 2060 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 31.7499\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 31.7183\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 31.6863\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 173ms/step - loss: 31.6542\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 31.6221\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 31.5901\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 31.5580\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 31.5260\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 31.4936\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 359ms/step - loss: 31.4619\n",
      "# 2070 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 31.4299\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 31.3978\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 31.3658\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 31.3338\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 31.3018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 31.2697\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 31.2374\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 31.2056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 31.1728\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 31.1409\n",
      "# 2080 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 31.1095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 31.0774\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 31.0454\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 31.0134\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 30.9813\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 124ms/step - loss: 30.9492\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 181ms/step - loss: 30.9172\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 30.8852\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 30.8531\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 30.8211\n",
      "# 2090 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 30.7891\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 30.7571\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 288ms/step - loss: 30.7249\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 30.6919\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 30.6598\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 30.6278\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 30.5958\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 672ms/step - loss: 30.5640\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 30.5319\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 30.4999\n",
      "# 2100 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 30.4675\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 30.4365\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 30.4045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 30.3722\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 150ms/step - loss: 30.3405\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 30.3077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 30.2755\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 351ms/step - loss: 30.2433\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 30.2123\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 416ms/step - loss: 30.1798\n",
      "# 2110 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 477ms/step - loss: 30.1483\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 30.1162\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 30.0830\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 158ms/step - loss: 30.0514\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 188ms/step - loss: 30.0192\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 29.9881\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 29.9555\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 29.9232\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 29.8911\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 628ms/step - loss: 29.8587\n",
      "# 2120 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 496ms/step - loss: 29.8271\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 470ms/step - loss: 29.7949\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 29.7630\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 177ms/step - loss: 29.7308\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 29.6984\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 29.6676\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 29.6345\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 29.6035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 29.5715\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 29.5395\n",
      "# 2130 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 29.5075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 29.4750\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 568ms/step - loss: 29.4426\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 29.4102\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 314ms/step - loss: 29.3782\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 180ms/step - loss: 29.3462\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 29.3141\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 276ms/step - loss: 29.2826\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 193ms/step - loss: 29.2510\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 240ms/step - loss: 29.2188\n",
      "# 2140 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 29.1867\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 29.1550\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 260ms/step - loss: 29.1229\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 779ms/step - loss: 29.0907\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 29.0589\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 29.0269\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 28.9945\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 28.9625\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 28.9305\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 28.8988\n",
      "# 2150 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 28.8667\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 28.8347\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 28.8027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 28.7706\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 28.7385\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 28.7065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 28.6742\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 28.6421\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 28.6100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 335ms/step - loss: 28.5780\n",
      "# 2160 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 28.5460\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 28.5140\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 28.4819\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 28.4499\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 28.4178\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 28.3858\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 28.3538\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 28.3217\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 28.2897\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 28.2576\n",
      "# 2170 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 28.2256\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 28.1935\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 28.1617\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 132ms/step - loss: 28.1294\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 28.0976\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 28.0657\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 28.0332\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 28.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 27.9697\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 27.9376\n",
      "# 2180 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 27.9056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 27.8736\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 27.8415\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 27.8095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 27.7775\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 27.7451\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 555ms/step - loss: 27.7130\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 27.6802\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 27.6490\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 167ms/step - loss: 27.6170\n",
      "# 2190 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 27.5849\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 27.5529\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 937ms/step - loss: 27.5210\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 27.4890\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 27.4568\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 27.4248\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 554ms/step - loss: 27.3927\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 27.3607\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 27.3288\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 27.2965\n",
      "# 2200 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 27.2649\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 98ms/step - loss: 27.2327\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 27.2006\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 27.1688\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 27.1367\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 27.1045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 27.0726\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 27.0406\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 27.0086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 26.9754\n",
      "# 2210 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 26.9445\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 26.9125\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 426ms/step - loss: 26.8804\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 26.8484\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 26.8164\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 26.7840\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 26.7523\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 26.7202\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 26.6876\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 26.6556\n",
      "# 2220 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 26.6236\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 26.5918\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 26.5597\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 26.5277\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 26.4957\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 26.4636\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 26.4316\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 26.3996\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 26.3675\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 26.3355\n",
      "# 2230 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 189ms/step - loss: 26.3030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 26.2710\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 26.2395\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 26.2074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 26.1755\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 209ms/step - loss: 26.1435\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 26.1113\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 26.0793\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 26.0474\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 26.0152\n",
      "# 2240 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 25.9833\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 25.9511\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 25.9191\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 25.8870\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 25.8550\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 25.8230\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 25.7909\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 25.7590\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 25.7268\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 25.6949\n",
      "# 2250 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 228ms/step - loss: 25.6628\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 25.6309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 25.5988\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 25.5668\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 25.5349\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 258ms/step - loss: 25.5023\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 25.4706\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 170ms/step - loss: 25.4386\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 25.4066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 25.3745\n",
      "# 2260 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 25.3428\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 25.3107\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 25.2787\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 25.2467\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 116ms/step - loss: 25.2146\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 25.1826\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 25.1505\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 25.1185\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 151ms/step - loss: 25.0865\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 25.0541\n",
      "# 2270 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 25.0216\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 24.9902\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 24.9584\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 24.9263\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 24.8943\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 24.8622\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 24.8295\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 24.7973\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 24.7659\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 24.7330\n",
      "# 2280 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 24.7014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 634ms/step - loss: 24.6696\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 707ms/step - loss: 24.6375\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 24.6054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 24.5734\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 24.5413\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 24.5099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 24.4780\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 24.4458\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 24.4138\n",
      "# 2290 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 24.3818\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 163ms/step - loss: 24.3497\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 24.3170\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 24.2850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 180ms/step - loss: 24.2530\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 24.2209\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 24.1889\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 24.1569\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 24.1255\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 24.0934\n",
      "# 2300 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 24.0614\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 24.0294\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 23.9973\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 23.9653\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 23.9333\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 23.9012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 418ms/step - loss: 23.8692\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 23.8372\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 23.8052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 23.7731\n",
      "# 2310 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 23.7411\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 479ms/step - loss: 23.7090\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 615ms/step - loss: 23.6762\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 23.6444\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 23.6127\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 23.5806\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 23.5486\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 23.5164\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 23.4848\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 23.4523\n",
      "# 2320 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 152ms/step - loss: 23.4204\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 23.3886\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 23.3563\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 23.3243\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 23.2923\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 23.2603\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 23.2278\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 23.1958\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 23.1642\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 23.1323\n",
      "# 2330 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 190ms/step - loss: 23.1002\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 23.0681\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 23.0362\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 23.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 22.9720\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 22.9400\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 22.9079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 22.8759\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 22.8438\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 22.8118\n",
      "# 2340 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 22.7801\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 22.7474\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 22.7158\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 22.6838\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 22.6518\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 22.6195\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 22.5877\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 22.5557\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 22.5236\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 22.4916\n",
      "# 2350 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 22.4596\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 22.4275\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 870ms/step - loss: 22.3954\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 22.3633\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 22.3312\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 22.2994\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 22.2672\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 22.2353\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 22.2030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 22.1715\n",
      "# 2360 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 22.1395\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 22.1075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 22.0755\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 22.0434\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 22.0114\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 21.9794\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 21.9474\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 512ms/step - loss: 21.9142\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 441ms/step - loss: 21.8821\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 963ms/step - loss: 21.8501\n",
      "# 2370 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 165ms/step - loss: 21.8187\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 21.7869\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 21.7548\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 21.7228\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 21.6907\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 21.6590\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 21.6267\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 21.5947\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 21.5625\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 21.5308\n",
      "# 2380 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 21.4989\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 21.4669\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 184ms/step - loss: 21.4346\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 234ms/step - loss: 21.4020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 21.3703\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 21.3381\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 21.3064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 486ms/step - loss: 21.2742\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 233ms/step - loss: 21.2424\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 21.2102\n",
      "# 2390 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 21.1780\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 21.1464\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 21.1142\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 337ms/step - loss: 21.0825\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 21.0504\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 21.0181\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 20.9862\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 20.9542\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 20.9221\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 20.8902\n",
      "# 2400 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 342ms/step - loss: 20.8571\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 20.8260\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 773ms/step - loss: 20.7941\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 20.7620\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 20.7302\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 20.6980\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 20.6661\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 249ms/step - loss: 20.6342\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 822ms/step - loss: 20.6020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 20.5701\n",
      "# 2410 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 141ms/step - loss: 20.5380\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 20.5060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 20.4740\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 20.4416\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 20.4099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 20.3779\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 20.3453\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 20.3132\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 20.2812\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 20.2495\n",
      "# 2420 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 20.2175\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 20.1855\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 20.1534\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 20.1214\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 20.0896\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 20.0573\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 20.0255\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 19.9935\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 19.9615\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 19.9289\n",
      "# 2430 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 19.8974\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 832ms/step - loss: 19.8649\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 19.8328\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 19.8009\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 19.7683\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 19.7370\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 19.7051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 19.6730\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 19.6410\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 19.6092\n",
      "# 2440 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 19.5770\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 19.5451\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 19.5128\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 212ms/step - loss: 19.4809\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 19.4488\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 19.4168\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 19.3850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 19.3527\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 19.3208\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 19.2888\n",
      "# 2450 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 19.2566\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 19.2246\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 19.1926\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 19.1606\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 19.1286\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 19.0965\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 19.0644\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 19.0324\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 19.0005\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 18.9685\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# 2460 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 18.9364\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 18.9044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 18.8724\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 18.8404\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 18.8083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 18.7765\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 18.7445\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 18.7124\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 18.6804\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 18.6480\n",
      "# 2470 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 18.6163\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 18.5843\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 18.5524\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 90ms/step - loss: 18.5203\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 18.4876\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 18.4556\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 18.4239\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 18.3917\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 18.3597\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 18.3278\n",
      "# 2480 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 18.2959\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 18.2638\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 18.2318\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 18.1997\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 18.1673\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 18.1356\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 18.1037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 18.0716\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 18.0396\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 18.0067\n",
      "# 2490 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 645ms/step - loss: 17.9748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 17.9426\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 468ms/step - loss: 17.9108\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 17.8797\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 17.8475\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 17.8150\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 17.7836\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 220ms/step - loss: 17.7506\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 17.7194\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 17.6874\n",
      "# 2500 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 17.6553\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 17.6234\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 17.5912\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 342ms/step - loss: 17.5593\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 302ms/step - loss: 17.5273\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 17.4952\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 17.4632\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 17.4314\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 17.3992\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 398ms/step - loss: 17.3674\n",
      "# 2510 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 17.3351\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 166ms/step - loss: 17.3021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 17.2708\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 17.2392\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 17.2070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 681ms/step - loss: 17.1750\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 17.1428\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 17.1109\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 17.0788\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 17.0470\n",
      "# 2520 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 17.0146\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 16.9826\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 16.9503\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 16.9187\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 16.8866\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 16.8544\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 16.8229\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 16.7906\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 710ms/step - loss: 16.7585\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 529ms/step - loss: 16.7268\n",
      "# 2530 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 197ms/step - loss: 16.6945\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 16.6624\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 16.6303\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 16.5985\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 16.5663\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 16.5344\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 16.5024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 16.4703\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 16.4383\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 16.4064\n",
      "# 2540 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 16.3743\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 16.3423\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 16.3103\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 16.2785\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 16.2465\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 16.2144\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 16.1824\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 16.1504\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 16.1184\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 16.0864\n",
      "# 2550 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 16.0543\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 16.0223\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 15.9903\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 15.9583\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 358ms/step - loss: 15.9261\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 15.8936\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 15.8616\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 15.8296\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 15.7978\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 15.7658\n",
      "# 2560 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 15.7338\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 15.7017\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 15.6698\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 15.6377\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 277ms/step - loss: 15.6058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 15.5735\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 15.5417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 15.5096\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 747ms/step - loss: 15.4776\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 15.4456\n",
      "# 2570 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 15.4135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 15.3815\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 15.3496\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 15.3171\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 15.2855\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 15.2535\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 15.2216\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 15.1894\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 211ms/step - loss: 15.1573\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 15.1253\n",
      "# 2580 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 15.0933\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 648ms/step - loss: 15.0611\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 169ms/step - loss: 15.0291\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 543ms/step - loss: 14.9971\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 14.9652\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 14.9332\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 14.9011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 14.8692\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 14.8371\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 14.8050\n",
      "# 2590 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 14.7731\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 14.7407\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 14.7091\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 14.6771\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 14.6450\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 14.6131\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 14.5809\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 14.5490\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 14.5170\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 14.4845\n",
      "# 2600 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 14.4525\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 14.4204\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 14.3884\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 14.3564\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 14.3250\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 14.2929\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 14.2604\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 14.2284\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 14.1963\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 582ms/step - loss: 14.1648\n",
      "# 2610 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 14.1327\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 861ms/step - loss: 14.1007\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 14.0686\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 14.0367\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 14.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 13.9724\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 13.9405\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 13.9087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 13.8764\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 13.8445\n",
      "# 2620 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 518ms/step - loss: 13.8124\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 273ms/step - loss: 13.7804\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 13.7485\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 13.7166\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 13.6843\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 13.6523\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 13.6203\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 209ms/step - loss: 13.5885\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 13.5562\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 13.5243\n",
      "# 2630 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 13.4923\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 13.4600\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 13.4282\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 158ms/step - loss: 13.3964\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 13.3641\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 13.3321\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 13.3000\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 13.2680\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 13.2360\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 308ms/step - loss: 13.2041\n",
      "# 2640 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 821ms/step - loss: 13.1721\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 321ms/step - loss: 13.1401\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 13.1081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 104ms/step - loss: 13.0761\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 13.0439\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 13.0119\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 12.9799\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 12.9477\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 12.9159\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 12.8838\n",
      "# 2650 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 12.8514\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 12.8196\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 12.7878\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 12.7557\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 12.7236\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 12.6916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 12.6596\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 12.6276\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 209ms/step - loss: 12.5956\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 12.5636\n",
      "# 2660 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 12.5316\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 12.4995\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 911ms/step - loss: 12.4676\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 195ms/step - loss: 12.4356\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 178ms/step - loss: 12.4035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 12.3716\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 12.3396\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 12.3074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 12.2753\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 250ms/step - loss: 12.2434\n",
      "# 2670 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 12.2113\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 12.1792\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 12.1473\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 12.1153\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 12.0831\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 12.0513\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 12.0192\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 174ms/step - loss: 11.9873\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 11.9551\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 11.9231\n",
      "# 2680 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 11.8910\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 11.8590\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 11.8269\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 11.7949\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 11.7630\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 11.7309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 11.6990\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 11.6667\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 11.6348\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 11.6028\n",
      "# 2690 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 11.5709\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 11.5389\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 300ms/step - loss: 11.5070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 11.4748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 11.4427\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 11.4110\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 11.3786\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 11.3470\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 11.3150\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 11.2830\n",
      "# 2700 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 11.2509\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 11.2182\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 11.1866\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 208ms/step - loss: 11.1546\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 11.1225\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 11.0906\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 11.0585\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 11.0265\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 10.9944\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 10.9625\n",
      "# 2710 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 10.9304\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 10.8987\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 10.8667\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 10.8347\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 10.8025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 10.7705\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 10.7386\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 10.7059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 10.6739\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 10.6419\n",
      "# 2720 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 346ms/step - loss: 10.6099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 10.5779\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 10.5461\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 297ms/step - loss: 10.5144\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 174ms/step - loss: 10.4822\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 167ms/step - loss: 10.4503\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 227ms/step - loss: 10.4182\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 223ms/step - loss: 10.3860\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 272ms/step - loss: 10.3541\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 10.3223\n",
      "# 2730 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 10.2900\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 10.2575\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 10.2260\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 10.1938\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 10.1621\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 10.1298\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 10.0981\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 10.0658\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 10.0339\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 10.0021\n",
      "# 2740 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 9.9698\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 9.9377\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 9.9057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 9.8739\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 9.8416\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 9.8097\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 9.7778\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 9.7458\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 9.7138\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 9.6817\n",
      "# 2750 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 9.6497\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 670ms/step - loss: 9.6177\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 907ms/step - loss: 9.5857\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 168ms/step - loss: 9.5536\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 9.5217\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 9.4896\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 9.4569\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 9.4256\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 9.3931\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 9.3611\n",
      "# 2760 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 9.3291\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 9.2971\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 137ms/step - loss: 9.2655\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 9.2331\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 9.2010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 9.1691\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 128ms/step - loss: 9.1376\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 9.1054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 9.0732\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 389ms/step - loss: 9.0411\n",
      "# 2770 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 9.0091\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 8.9771\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 8.9451\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 8.9131\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 8.8811\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 8.8491\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 8.8171\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 8.7850\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 8.7531\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 8.7210\n",
      "# 2780 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 8.6887\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 8.6569\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 8.6252\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 8.5926\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 8.5609\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 8.5289\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 8.4969\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 8.4651\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 8.4328\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 8.4008\n",
      "# 2790 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 8.3688\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 8.3369\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 8.3050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 8.2727\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 8.2410\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 8.2083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 8.1769\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 108ms/step - loss: 8.1442\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 8.1126\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 8.0808\n",
      "# 2800 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 8.0487\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 8.0166\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 7.9846\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 7.9526\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 7.9202\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 7.8887\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 7.8566\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 7.8246\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 7.7924\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 7.7607\n",
      "# 2810 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 7.7285\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 7.6965\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 7.6645\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 7.6325\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 7.6003\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 7.5685\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 7.5367\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 180ms/step - loss: 7.5045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 198ms/step - loss: 7.4726\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 7.4405\n",
      "# 2820 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 7.4084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 7.3764\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 7.3443\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 7.3125\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 7.2805\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 298ms/step - loss: 7.2485\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 7.2165\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 7.1844\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 416ms/step - loss: 7.1525\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 449ms/step - loss: 7.1203\n",
      "# 2830 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 7.0884\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 7.0564\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 7.0243\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 6.9917\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 6.9596\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 6.9277\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 6.8961\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 6.8638\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 6.8316\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 6.7996\n",
      "# 2840 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 6.7677\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 6.7358\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 6.7039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 6.6715\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 6.6396\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 6.6080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 6.5759\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 6.5437\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 6.5120\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 6.4798\n",
      "# 2850 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 6.4479\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 6.4157\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 6.3837\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 6.3517\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 6.3196\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 6.2876\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 6.2555\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 6.2240\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 6.1916\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 6.1596\n",
      "# 2860 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 6.1277\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 6.0956\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 6.0634\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 6.0314\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 5.9995\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 5.9676\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 105ms/step - loss: 5.9354\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 5.9037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 5.8715\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 5.8396\n",
      "# 2870 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 5.8075\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 5.7757\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 5.7435\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 276ms/step - loss: 5.7104\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 881ms/step - loss: 5.6793\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 5.6475\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 5.6153\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 5.5835\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 5.5514\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 5.5194\n",
      "# 2880 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 109ms/step - loss: 5.4871\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 145ms/step - loss: 5.4547\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 5.4232\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 97ms/step - loss: 5.3912\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 731ms/step - loss: 5.3587\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 5.3266\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 351ms/step - loss: 5.2951\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 5.2631\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 5.2311\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 5.1991\n",
      "# 2890 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 5.1669\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 139ms/step - loss: 5.1353\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 5.1031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 5.0712\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 5.0392\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 5.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 4.9751\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 4.9432\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 4.9111\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 4.8790\n",
      "# 2900 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 4.8471\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 4.8151\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 4.7831\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 4.7511\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 4.7191\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 4.6870\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 4.6545\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 4.6230\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 4.5904\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 4.5584\n",
      "# 2910 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 4.5268\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 4.4948\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 4.4629\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 483ms/step - loss: 4.4303\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 4.3989\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 4.3664\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 4.3349\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 4.3028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 4.2709\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 4.2386\n",
      "# 2920 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 4.2068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 216ms/step - loss: 4.1748\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 4.1421\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 132ms/step - loss: 4.1107\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 4.0783\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 4.0464\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 4.0147\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 3.9826\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 3.9507\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 3.9187\n",
      "# 2930 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 3.8866\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 3.8546\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 3.8226\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 3.7906\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 3.7586\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 3.7265\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 383ms/step - loss: 3.6945\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 3.6626\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 3.6305\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 3.5982\n",
      "# 2940 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 3.5665\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 263ms/step - loss: 3.5345\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 3.5024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 3.4703\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 3.4385\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 104ms/step - loss: 3.4064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 3.3744\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 3.3424\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 316ms/step - loss: 3.3103\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 3.2783\n",
      "# 2950 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 3.2463\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 3.2143\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 3.1823\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 250ms/step - loss: 3.1502\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 3.1176\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 3.0856\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 3.0541\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 3.0222\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 2.9898\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 2.9575\n",
      "# 2960 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 2.9258\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 2.8939\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 2.8618\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 2.8299\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 2.7980\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 2.7661\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 2.7339\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 2.7020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 2.6698\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 2.6380\n",
      "# 2970 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 2.6055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 2.5736\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 2.5417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 2.5094\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 2.4775\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 2.4459\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 2.4137\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 2.3818\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 2.3495\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 2.3178\n",
      "# 2980 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 2.2857\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 2.2537\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 2.2217\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 2.1895\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 2.1575\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 2.1252\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 2.0934\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 2.0615\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 2.0295\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 1.9975\n",
      "# 2990 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 1.9656\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 1.9335\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 1.9014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 1.8695\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 1.8376\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 1.8053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 1.7736\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 1.7416\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 1.7096\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 1.6776\n",
      "# 3000 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 1.6453\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 1.6133\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 1.5812\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 1.5492\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 494ms/step - loss: 1.5164\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 1.4854\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 1.4526\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 1.4212\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 1.3892\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 1.3572\n",
      "# 3010 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 1.3252\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 1.2931\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 1.2612\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 1.2293\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 1.1971\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 1.1650\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 1.1331\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 1.1011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 1.0691\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 1.0373\n",
      "# 3020 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 1.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.9733\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.9412\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.9092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.8765\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.8452\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.8132\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.7811\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.7493\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.7177\n",
      "# 3030 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.6853\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.6532\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.6209\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 190ms/step - loss: 0.5887\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.5574\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.5251\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.4921\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 0.4612\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.4291\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.3973\n",
      "# 3040 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.3651\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.3330\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 308ms/step - loss: 0.3013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.2692\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 291ms/step - loss: 0.2370\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.2051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.1736\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.1433\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.1128\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0767\n",
      "# 3050 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0458\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0435\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0318\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0434\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 581ms/step - loss: 0.0645\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0803\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0856\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0912\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0957\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 0.0927\n",
      "# 3060 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0867\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 193ms/step - loss: 0.0814\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0724\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0593\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0474\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0320\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0178\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0277\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0298\n",
      "# 3070 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 0.0396\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0427\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0382\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 0.0384\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0309\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0216\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0144\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 0.0190\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0134\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 297ms/step - loss: 0.0287\n",
      "# 3080 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0284\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0246\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0269\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 252ms/step - loss: 0.0172\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0195\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 947ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0305\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0362\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 0.0204\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0307\n",
      "# 3090 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0377\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0243\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0190\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0257\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 879ms/step - loss: 0.0298\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 875ms/step - loss: 0.0417\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0298\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0141\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0282\n",
      "# 3100 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0268\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0280\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0363\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0246\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0147\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0266\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 147ms/step - loss: 0.0239\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 0.0222\n",
      "# 3110 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0247\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0116\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0232\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0300\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 145ms/step - loss: 0.0203\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0091\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0170\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0171\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0223\n",
      "# 3120 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 190ms/step - loss: 0.0122\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0149\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0185\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0186\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0268\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 179ms/step - loss: 0.0188\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 149ms/step - loss: 0.0160\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0104\n",
      "# 3130 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0096\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0129\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0114\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0111\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0128\n",
      "# 3140 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 312ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 97ms/step - loss: 0.0165\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0205\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0112\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0117\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 124ms/step - loss: 0.0168\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0096\n",
      "# 3150 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0139\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0169\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0127\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0188\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0118\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 0.0114\n",
      "# 3160 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 709ms/step - loss: 0.0152\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0200\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0137\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 0.0141\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 320ms/step - loss: 0.0176\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0096\n",
      "# 3170 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0144\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0091\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 0.0133\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 0.0117\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0167\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0065\n",
      "# 3180 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 308ms/step - loss: 0.0027\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 678ms/step - loss: 0.0129\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 398ms/step - loss: 0.0178\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0110\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 46ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0102\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 0.0109\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0147\n",
      "# 3190 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0131\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 220ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0123\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0098\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0138\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 200ms/step - loss: 0.0084\n",
      "# 3200 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.0112\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 153ms/step - loss: 0.0104\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0139\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 417ms/step - loss: 0.0115\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0086\n",
      "# 3210 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0122\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 399ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 496ms/step - loss: 0.0121\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 310ms/step - loss: 0.0115\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0090\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0128\n",
      "# 3220 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 383ms/step - loss: 0.0072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 631ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 981ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0093\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0129\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 484ms/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0103\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 857ms/step - loss: 0.0052\n",
      "# 3230 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0123\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 658ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 362ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 458ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 0.0116\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 871ms/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0073\n",
      "# 3240 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0111\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 199ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0117\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0104\n",
      "# 3250 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 101ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 0.0077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 215ms/step - loss: 0.0109\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 716ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 178ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0113\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0061\n",
      "# 3260 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0100\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0074\n",
      "# 3270 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 242ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 379ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0103\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 152ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0096\n",
      "# 3280 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 349ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0098\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 90ms/step - loss: 0.0097\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 264ms/step - loss: 0.0097\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0052\n",
      "# 3290 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0090\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 752ms/step - loss: 0.0056\n",
      "# 3300 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 272ms/step - loss: 0.0086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 372ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 173ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 258ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 7s 7s/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0102\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 732ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0091\n",
      "# 3310 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 374ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 934ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 731ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0108\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0062\n",
      "# 3320 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0093\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 168ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0107\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0033\n",
      "# 3330 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 543ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 828ms/step - loss: 0.0117\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 509ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 0.0092\n",
      "# 3340 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 433ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 295ms/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 263ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 478ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 445ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 307ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0061\n",
      "# 3350 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 435ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 97ms/step - loss: 0.0085\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 371ms/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 247ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 0.0038\n",
      "# 3360 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 290ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 159ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 127ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 190ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 0.0107\n",
      "# 3370 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 257ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 244ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 289ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0106\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 714ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0026\n",
      "# 3380 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0059\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# 3390 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 967ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 535ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0057\n",
      "# 3400 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 199ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 306ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0046\n",
      "# 3410 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 0.0090\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 250ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0073\n",
      "# 3420 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 634ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 382ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 189ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0072\n",
      "# 3430 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 859ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0030\n",
      "# 3440 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 109ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0020\n",
      "# 3450 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 419ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 0.0103\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 355ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0055\n",
      "# 3460 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 318ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 163ms/step - loss: 0.0028\n",
      "# 3470 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 405ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 8.3347e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 780ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 9.2493e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0020\n",
      "# 3480 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 146ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 9.4596e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 212ms/step - loss: 0.0043\n",
      "# 3490 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0047\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0049\n",
      "# 3500 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 146ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 242ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0039\n",
      "# 3510 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 763ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 147ms/step - loss: 9.3037e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 371ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0029\n",
      "# 3520 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 9.4632e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 206ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0019\n",
      "# 3530 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 880ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 823ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 111ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 154ms/step - loss: 0.0023\n",
      "# 3540 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 9.8887e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 268ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0020\n",
      "# 3550 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 273ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 149ms/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0094\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0049\n",
      "# 3560 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 160ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0054\n",
      "# 3570 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0022\n",
      "# 3580 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 3.7115e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0104\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 137ms/step - loss: 0.0085\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 248ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0085\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 113ms/step - loss: 0.0117\n",
      "# 3590 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0093\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0036\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 124ms/step - loss: 0.0014\n",
      "# 3600 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 643ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 976ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 690ms/step - loss: 0.0038\n",
      "# 3610 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 7.0557e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0091\n",
      "# 3620 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0078\n",
      "# 3630 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0113\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 364ms/step - loss: 0.0087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 240ms/step - loss: 0.0077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0109\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0095\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0066\n",
      "# 3640 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 175ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0055\n",
      "# 3650 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0011\n",
      "# 3660 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 7.1078e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 0.0017\n",
      "# 3670 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0110\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0085\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0094\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 167ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0071\n",
      "# 3680 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 206ms/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 109ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 9.5590e-04\n",
      "# 3690 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 676ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0080\n",
      "# 3700 examples trained\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 459ms/step - loss: 0.0086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 146ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0057\n",
      "# 3710 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 356ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 647ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0098\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0031\n",
      "# 3720 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 7.5476e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0112\n",
      "# 3730 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 193ms/step - loss: 0.0103\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 8.5721e-04\n",
      "# 3740 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0118\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 90ms/step - loss: 0.0113\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 614ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 442ms/step - loss: 0.0074\n",
      "# 3750 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 5.3712e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0050\n",
      "# 3760 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 98ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0039\n",
      "# 3770 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 120ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 661ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 338ms/step - loss: 0.0012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 575ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 547ms/step - loss: 0.0013\n",
      "# 3780 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 826ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 8.0949e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0042\n",
      "# 3790 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0043\n",
      "# 3800 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 519ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0031\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 363ms/step - loss: 0.0025\n",
      "# 3810 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 477ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 551ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 562ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0028\n",
      "# 3820 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 863ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 164ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 793ms/step - loss: 0.0024\n",
      "# 3830 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 456ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 156ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 200ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 0.0038\n",
      "# 3840 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 523ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 0.0035\n",
      "# 3850 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 848ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 151ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 554ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 176ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0054\n",
      "# 3860 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 137ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 754ms/step - loss: 0.0085\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0047\n",
      "# 3870 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 426ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 246ms/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 102ms/step - loss: 0.0041\n",
      "# 3880 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0050\n",
      "# 3890 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 316ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0036\n",
      "# 3900 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 189ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 163ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 262ms/step - loss: 0.0011\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 0.0031\n",
      "# 3910 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 152ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 824ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 618ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0021\n",
      "# 3920 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 337ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 347ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 203ms/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 311ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 959ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 661ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0037\n",
      "# 3930 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 642ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 759ms/step - loss: 0.0072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 4.8642e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 7.0153e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0052\n",
      "# 3940 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0014\n",
      "# 3950 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 0.0046\n",
      "# 3960 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 215ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 137ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 896ms/step - loss: 0.0011\n",
      "# 3970 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0123\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0120\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 198ms/step - loss: 0.0077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 6.3203e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 108ms/step - loss: 0.0088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 175ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 8.5523e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 139ms/step - loss: 0.0070\n",
      "# 3980 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0094\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0120\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0117\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 132ms/step - loss: 0.0094\n",
      "# 3990 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 7.8961e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 0.0099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0139\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0135\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0093\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0128\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0131\n",
      "# 4000 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 238ms/step - loss: 0.0094\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0132\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0136\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 0.0087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0142\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0153\n",
      "# 4010 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0122\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0105\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0078\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0106\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0087\n",
      "# 4020 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0106\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0102\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0064\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0035\n",
      "# 4030 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 6.4263e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0066\n",
      "# 4040 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 94ms/step - loss: 0.0012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0044\n",
      "# 4050 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0014\n",
      "# 4060 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 3.8611e-04\n",
      "# 4070 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 264ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 94ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 272ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 0.0019\n",
      "# 4080 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 108ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0093\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0054\n",
      "# 4090 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0017\n",
      "# 4100 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 2.2325e-05\n",
      "# 4110 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 188ms/step - loss: 1.9220e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0082\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 202ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 128ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 6s 6s/step - loss: 0.0049\n",
      "# 4120 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 207ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 603ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 263ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 299ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0038\n",
      "# 4130 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 624ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 94ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 5.5606e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 4.0644e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 116ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 412ms/step - loss: 0.0019\n",
      "# 4140 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 285ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 158ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 152ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0036\n",
      "# 4150 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 6.1174e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 572ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0047\n",
      "# 4160 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0012\n",
      "# 4170 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 635ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 327ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 908ms/step - loss: 0.0039\n",
      "# 4180 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 377ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 122ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 293ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 369ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0031\n",
      "# 4190 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 297ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0013\n",
      "# 4200 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 285ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0010\n",
      "# 4210 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 203ms/step - loss: 7.9954e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0016\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 183ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0019\n",
      "# 4220 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 259ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 228ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 224ms/step - loss: 8.8659e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0055\n",
      "# 4230 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 300ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0079\n",
      "# 4240 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 6.8078e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 699ms/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0107\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0094\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0056\n",
      "# 4250 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0091\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 792ms/step - loss: 5.1295e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 82ms/step - loss: 0.0087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0125\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0115\n",
      "# 4260 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0031\n",
      "# 4270 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 5.7366e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 873ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0076\n",
      "# 4280 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 139ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 213ms/step - loss: 0.0086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0108\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0099\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 0.0086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 0.0041\n",
      "# 4290 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 824ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 360ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 204ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 0.0020\n",
      "# 4300 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 547ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 6.5289e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 688ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 144ms/step - loss: 8.5766e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 157ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 201ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 836ms/step - loss: 8.5941e-04\n",
      "# 4310 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 127ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 95ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 279ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0034\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# 4320 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 700ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 150ms/step - loss: 0.0026\n",
      "# 4330 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 171ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0073\n",
      "# 4340 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 313ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 1.0519e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0021\n",
      "# 4350 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 291ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 7.9590e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 901ms/step - loss: 0.0029\n",
      "# 4360 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 716ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 251ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 582ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 151ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0021\n",
      "# 4370 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 588ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 154ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 141ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 271ms/step - loss: 0.0014\n",
      "# 4380 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 313ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 156ms/step - loss: 6.3817e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 420ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0035\n",
      "# 4390 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 404ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 168ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 104ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0032\n",
      "# 4400 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 4.0762e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 5s 5s/step - loss: 0.0024\n",
      "# 4410 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 100ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 5.1118e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 86ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 101ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 135ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0028\n",
      "# 4420 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 0.0020\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0026\n",
      "# 4430 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 300ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 728ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 830ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 283ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 678ms/step - loss: 0.0029\n",
      "# 4440 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 578ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 696ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 383ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0077\n",
      "# 4450 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 211ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 118ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0035\n",
      "# 4460 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 382ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0016\n",
      "# 4470 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 306ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 390ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 486ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 3s 3s/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0045\n",
      "# 4480 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 130ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0056\n",
      "# 4490 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 171ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 180ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 124ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0029\n",
      "# 4500 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 92ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 602ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0032\n",
      "# 4510 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 913ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 611ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 7.5862e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0083\n",
      "# 4520 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0065\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 212ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0047\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 138ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 159ms/step - loss: 8.8611e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0059\n",
      "# 4530 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 311ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 141ms/step - loss: 0.0013\n",
      "# 4540 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 500ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 101ms/step - loss: 9.9987e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 164ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 599ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0025\n",
      "# 4550 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 212ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 6.5832e-04\n",
      "# 4560 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 165ms/step - loss: 0.0072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 127ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 0.0042\n",
      "# 4570 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 298ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 196ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 53ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0041\n",
      "# 4580 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 188ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 45ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0047\n",
      "# 4590 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 129ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0035\n",
      "# 4600 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 181ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0031\n",
      "# 4610 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 598ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0067\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0055\n",
      "# 4620 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 350ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 320ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 142ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 182ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 324ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0079\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0054\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# 4630 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 109ms/step - loss: 8.0953e-04\n",
      "# 4640 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 61ms/step - loss: 0.0086\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 43ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 171ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0070\n",
      "# 4650 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 8.5166e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 138ms/step - loss: 0.0087\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0130\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 132ms/step - loss: 0.0125\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 400ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0082\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0014\n",
      "# 4660 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 8.1917e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0078\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0107\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 145ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0083\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 0.0126\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0118\n",
      "# 4670 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0040\n",
      "# 4680 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 397ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 172ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0074\n",
      "# 4690 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 93ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 126ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0027\n",
      "# 4700 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 110ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 186ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 238ms/step - loss: 8.5741e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 770ms/step - loss: 7.9942e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 140ms/step - loss: 0.0101\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 49ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 9.8901e-04\n",
      "# 4710 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0078\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0108\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 162ms/step - loss: 0.0091\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 146ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 486ms/step - loss: 0.0094\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0090\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0068\n",
      "# 4720 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 109ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 75ms/step - loss: 0.0067\n",
      "# 4730 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0045\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 207ms/step - loss: 0.0077\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0052\n",
      "# 4740 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 3.1891e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0019\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 132ms/step - loss: 5.3942e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 116ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 87ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 8.7403e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0058\n",
      "# 4750 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0071\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0041\n",
      "# 4760 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 119ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 97ms/step - loss: 0.0070\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 57ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 83ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0027\n",
      "# 4770 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 88ms/step - loss: 0.0048\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0027\n",
      "# 4780 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 229ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0075\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 0.0051\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 487ms/step - loss: 0.0055\n",
      "# 4790 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 115ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0032\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 4.0561e-04\n",
      "# 4800 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 8.5950e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 330ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 9.9070e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0073\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0088\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 154ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 199ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0082\n",
      "# 4810 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0018\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0066\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0084\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 134ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0074\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 54ms/step - loss: 0.0036\n",
      "# 4820 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 103ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0047\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0076\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 133ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0059\n",
      "# 4830 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 117ms/step - loss: 6.5552e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0069\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0083\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0012\n",
      "# 4840 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0092\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 141ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 91ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 50ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0048\n",
      "# 4850 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0061\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0052\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0067\n",
      "# 4860 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 47ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 276ms/step - loss: 0.0078\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 84ms/step - loss: 0.0045\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 194ms/step - loss: 0.0057\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 254ms/step - loss: 0.0036\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0023\n",
      "# 4870 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0024\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 764ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 185ms/step - loss: 5.0151e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 107ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 258ms/step - loss: 0.0062\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 131ms/step - loss: 0.0023\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 113ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0081\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 121ms/step - loss: 0.0013\n",
      "# 4880 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 493ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 161ms/step - loss: 0.0059\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 104ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 454ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 228ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 330ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0034\n",
      "# 4890 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0080\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 4.9446e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 71ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 114ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0061\n",
      "# 4900 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0072\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 69ms/step - loss: 0.0056\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 9.5157e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 260ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 44ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 172ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 124ms/step - loss: 0.0060\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0015\n",
      "# 4910 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 74ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 148ms/step - loss: 0.0089\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0063\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0078\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0046\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 147ms/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 80ms/step - loss: 0.0022\n",
      "# 4920 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0068\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0055\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 172ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0053\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 76ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0041\n",
      "# 4930 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 106ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 90ms/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 155ms/step - loss: 0.0043\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0058\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 158ms/step - loss: 0.0050\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 0.0021\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 228ms/step - loss: 0.0057\n",
      "# 4940 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 68ms/step - loss: 0.0039\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 78ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 96ms/step - loss: 0.0054\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0049\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 112ms/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 73ms/step - loss: 0.0030\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 386ms/step - loss: 0.0018\n",
      "# 4950 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 70ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0010\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 8.2701e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 65ms/step - loss: 0.0014\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 48ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 89ms/step - loss: 0.0013\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 125ms/step - loss: 9.0926e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 236ms/step - loss: 0.0026\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 77ms/step - loss: 0.0022\n",
      "# 4960 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 352ms/step - loss: 0.0021\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 99ms/step - loss: 0.0031\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 232ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0025\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 72ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 60ms/step - loss: 0.0011\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0037\n",
      "# 4970 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 56ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 5.4458e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0029\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0015\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 66ms/step - loss: 0.0041\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 85ms/step - loss: 0.0040\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 159ms/step - loss: 8.8943e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 59ms/step - loss: 0.0012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0037\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 46ms/step - loss: 0.0024\n",
      "# 4980 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0042\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 162ms/step - loss: 0.0044\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 64ms/step - loss: 2.4732e-04\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 79ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 67ms/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 62ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 51ms/step - loss: 0.0012\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 81ms/step - loss: 0.0016\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0026\n",
      "# 4990 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0017\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 58ms/step - loss: 0.0035\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 266ms/step - loss: 0.0034\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 4s 4s/step - loss: 0.0020\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0038\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 204ms/step - loss: 0.0028\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 2s 2s/step - loss: 0.0033\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 63ms/step - loss: 0.0027\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 55ms/step - loss: 0.0022\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 0s 52ms/step - loss: 0.0022\n",
      "# 5000 examples trained\n",
      "Epoch 1/1\n",
      "1/1 [==============================] - 1s 1s/step - loss: 0.0027\n"
     ]
    }
   ],
   "source": [
    "counter = 0\n",
    "loss = []\n",
    "for x_seq,label in zip(X_train,Y_train):\n",
    "    counter +=1\n",
    "    if counter %10 ==0:\n",
    "        print(\"# {} examples trained\".format(counter))\n",
    "    X_seq = np.array(x_seq).reshape(-1,len(x_seq), 2)\n",
    "    y = np.array(label).reshape(1, 2) # predict next element\n",
    "    history = model.fit(X_seq, y, batch_size=1, verbose=1, shuffle=False)\n",
    "    loss.extend(history.history['loss'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loss VS # of training examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tzoix03zIb+fKsaxLsGa2lNDH7CJCYl0LTAHWJHQ0swRolZkIS69+zarcfGIPZi1f70N+O1eOZV2CldSQMO5XO6AlUBsYXMimhV6Ak3SBpMmSJq9cuTJ9gZbSgC7NOTEa8nv60rWZDsc5lwZZl2CBgcB8M1tpZj8ATwMHAw2ikgFAa+Crwl5sZmPMrI+Z9WnatGnZRFxC1xzblQa1qjF87DS2bPV7NZwrb7IxwS4CDpRUKxoOfAAwA3gDGBZtczbwbIbiS5kGtapx04ndmblsHfdNnJvpcJxzKZZ1CdbMPiBczPqY0ESrEjAGuAK4VNIcoDGho5mcd3S3FhzbqyX3vDGbmcvWZToc51wKxR30sLKksyT9S9I4SftGyxtGy1Ny4cnMrjGzzmbW3czONLPNZjbPzPY3sw5mdoqZbU7Fe2WD647rRr0aVRk+dio/bPNSgXPlRZxBD2sBbwIPEy5CHQE0jFavA24BLkpxfBVCo9rVuOGE7kxfuo4xk0pyh7JzLhvFOYO9FuhDGFG2PaGrQgDMbBvhYtTRqQyuIhnSI49jeuRx9+uz+XL5+kyH45xLgTgJ9hRgjJk9CxT2O3YO0DYVQVVU1x3fjTo1qjD8yals9VKBczkvToJtCUwtZv33hIEPXQk1qVOda4/rxtQla/nb2/MzHY5zrpTiJNhvKP7uqW4U0TbVJe/Ynnkc3a05fxr3JXNWfJfpcJxzpRAnwY4Hzo0udu1EUjvg58ArqQqsopLEDSd0p1a1ygwfO5Vt273HSOdyVZwEex2h1cBHhNYCBgySNIrQZnUzMCrlEVZAzerW4Jpju/LJojU89I6XCpzLVXFGlZ1DuKtqK3A9oRXB5YQbABYDA8xscTqCrIhO2KcVA7s047ZXZzF/1YZMh+OcK4FYNxqY2RQz6wX0BE4l9NPa28x6mllxF8BcTJK46cQeVK9SiRFjp7LdSwXO5ZwS3SprZtPN7MloZNlPUh2UC5rXq8Efh3blowXf8sh7CzIdjnMupjh3cg2I6q1FrR8l6fDUhOXyDevdmv6dmjL6lVks/MZLBc7lkjhnsFcAHYpZ3y7axqWQJEad1IMqlcSIsdO8VOBcDomTYHsB7xez/oNoG5diefVrcvUxXfhg/mr+/cHCTIfjnEtSnARbHyjuN+pGdnT+4lLs1J/sQd+OTRj18hcsXv19psNxziUhToJdCvQuZn1v4OvSheOKIolbTu6JgJFPT8PMSwXOZbs4CfZF4GxJAwuukDSAMMrAS6kKzO2qVYOaXDmkC+/M+YbHPvQmx85luyq73+RHNwEnA69Kehn4lHA3176EQQm/Bm5IeYRuJ2fs34aXPlvGzS/N5LBOTWnVoGamQ3LOFSHOnVzLCYMPvkpIqFcBV0fPXwYOMbNl6QjS7VCpkrj15J5sN2PkU14qcC6bxb2Ta6GZDQGaAAcABwJNzGyomS1IQ3yuEHs0qsUVgzrz1uxVPDl5SabDcc4VoaR3cn1rZh+Z2Ydm9m2qg3K7d+aBe7J/u0bc8OIMlq3dmOlwnHOFiJ1go+G0u0rqK6lfwSkdQbpdVaokRp/ckx+2beeqpz/zUoFzWSjpi1xRP7B/As4t4nUiXPSqnJrQ3O60bVKb4Ud35oYXZvD0x0s5uXfrTIfknEsQpxXB3cB5hKZYEwgjHLgMO+fgtrz82TKue/5z+nZsQrN6NTIdknMuEifBngA8ZmY/TVcwLr7KlcToYT0ZfPdbXPXMdB48qzeSdv9C51zaxanB1gQmpikOVwrtm9bh8qM68frM5Tw31YdFcy5bxEmwk4GO6QrElc7PD23Hvm0acM1zn7Ni/aZMh+OcI16CHUkY9PAn6QrGlVzlSuK2YT35fss2/u9/n3urAueyQJwa7AXAEuA9Se8B84BtBbYxMzsvVcG5eDo0q8vvB+7Nra98wYufLWNoz5aZDsm5Ck3JnulI2p7EZmZmWdNMq0+fPjZ58uRMh1Gmtm7bzsn3vcvibzcy7vf9aFyneqZDcq7ckTTFzPrsbrs4fRFUSmLKmuRaUVWpXInRw3qxftMP/N9zn2c6HOcqtBLdKuuyW6cWdfndgI68OG0ZL3/m/e84lymeYMupXx62F91a1uOPz05n9YYtmQ7HuQopVoKV1FDS5ZKelPS6pAkFpvHpCtTFU7VyJW4b1os13//Adc97qcC5TIjTF8GewDtAS2AtUA9YTRiHqxKwiuLH7HJlrGvLelx8RAfuen02x/TI46huLTIdknMVSpwz2BuBBsAAwg0HAk4lJNpRwHqgb6oDdKXzq/4d6NyiLlf/bzprvvdSgXNlKU6CHQA8aGZvEHrNgtDM63szuxr4DLg11QG60qlWpRK3n9KL1Ru2cP0LMzIdjnMVSpwE2xiYHj3/IXpMHBBqHHBkKoJyqdW9VX1+1X8vnv54KRO+WJ7pcJyrMOIk2JVAo+j5emAT0DZhfTV2Trgui1x8RAc6Na/LlU9/xtrvf9j9C5xzpRYnwX4O9IJwuxbwIfArSW0ktSXcSvtFqgN0qVG9SmVuP6UXq77zUoFzZSVOgn0WOEhS/lnq9YSLXfOBudHzlAzbLamBpLGSvpA0U9JBkhpJGidpdvTYMBXvVZH0aF2fiw7bi6c+XuKlAufKQJxbZe81s73MbGM0PwE4iDDSwZ+Afmb2XIriuht4xcw6E86aZxJ68xpvZh2B8dG8i+k3AxJKBRu9VOBcOpXqTi4zm2xml5rZcDN7NxUBSaoH9AP+Hr3HFjNbAxwPPBJt9ghhhAUXU/UqlbntlJ6s+m4LN3ipwLm0SjrBSpon6bhi1g+VNC8FMbUnXFB7SNInkv4mqTbQ3MyWAUSPzVLwXhVSz9YNuPCw9oydsoQ3vliR6XCcK7finMG2BeoUs742sGepogmqAPsB95nZvoS7w5IuB0i6QNJkSZNXrlyZgnDKp98O6Mjezet4qcC5NEplZy/Nge9TsJ8lwBIz+yCaH0tIuMsl5QFEj4WeepnZGDPrY2Z9mjZtmoJwyqf8VgUrv9vMjV4qcC4tiu2LQFI/oH/CopMkdShk00bAacCnpQ3IzL6WtFhSJzObRbiDbEY0nQ3cEj0+W9r3quh6tm7AL/u1596JcxnSM4/DO3nVxblUKnZEA0nXANdEs0bof6Aoc4AzzKzUQwhI2gf4G+HmhXnAuYSz7f8CbYBFwClmtrq4/VTEEQ3i2rx1G0P//DbrN23ltUv7Ua9G1UyH5FzWS3ZEg90l2PqEDl5ESHSXsOuZowHf7S7ZZYIn2ORMXbyGE+99h2G9WzN6WK9Mh+Nc1ks2wRZbIjCztYSuCZF0ODDTzPyycznTa48G/PKwvbhv4lyG9Mijv5cKnEuJODcavFlYcpXUW9KRkmqkNjRXli4Z2JGOzUKrgnWbvFWBc6kQpx3s5ZKeL7DsP4Q+CV4BPpPUPMXxuTISbkDoxfJ1m7jphZmZDse5ciFOM63TCBeXAJB0RLTsceBqIA8YkdLoXJnaZ48GXNBvL56YvJg3v/Q2xM6VVtwbDRJ7yzoBWAb8zMxuAe4Hjk1daC4TLhnYkQ7N6jDyqWleKnCulOIk2NrsfCPBEcDrtqMZwgygVaoCc5lRo2plbhvWk+XrNnHzi14qcK404iTYpUBP+HEAxK7AmwnrGwKbUxeay5R92zTk/H7tefyjxUzyUoFzJRYnwT4PXCjpHsLtq5uBFxPWdwcWpC40l0m/H7g3ezWt7aUC50ohToK9Hngb+BUhmV5iZssBok64TwTeSHmELiNqVA19FXy9bhOjXvJSgXMlUeyNBonM7FtgQNRf60YzK3hacxiwOJXBuczKLxU88OY8BnfPo9/e3nmOc3HE7k3LzNYVTK5mttHMpmbj7bKudBJLBeu9VOBcLEUm2GgwwzYF53c3lU3YrqzUqBpuQPh63SZufsnHtHQujuJKBAuA7ZJqmdmWaL7onmF2qJyCuFwW2a9NQ87v254HJs3jmB55HNqxSaZDci4nFJdgryck1K0F5l0F9Psj92bczOVc8dQ0XrmkL3W9W0PndqvY7gpznXdXmFpTFn7LKfe/y2n7t+HmE3tkOhznMibZ7gpTOWSMK+d679mQX/Rtz38+WMTbs1dlOhznsl6RJYKSXrAys0W738rlqkuP3JvXo1LBq7/vR53qSbf0c67CKe4MdgEwvwSTK8dCXwW9+GrtRr8BwbndSOYiV6LjgH2AcYTOXUTok2AAYcDD53HlXu89G/KLQ9vx4FvzGdIjj0M6eKsC5wpTZII1s2sT5yWdAbQDepvZpwXW7QeMB75MQ4wuC112VCfGz1zBiLFeKnCuKHEucl0B3FMwuQKY2cfAX4ErUxWYy27hBoSefLV2I7e87KUC5woTJ8HuDRQ34OFyoGPpwnG5pPeejTjvkHb86/1FvDvHWxU4V1CcBLsMOEmSCq6QVAk4Gfg6VYG53HDZUZ1o16Q2w8dO47vNW3f/AucqkDgJ9kGgP/CqpEGS2klqK2kw8CrQFxiThhhdFqtZLYyA8NXajdz6svdV4FyiOFcmbgGaA78htBoo6K9mNiolUbmc0qdtI35+SDv+/vZ8BndvwcHeqsA5oAS3ykraGzgeaE9opjUXeM7MZqU+vNLxW2XLzsYt2xjy57f4Ydt2Xr2kH7W9VYErx9J2q6yZfWlmt5nZRWZ2YfQ865KrK1s1q1Vm9LCeLF2zkVu8VOAc4H0RuBT6SdtGnHtwO/75/kLeneutCpzzBOtSavjRnWjbuBZXPDWNDd6qwFVwnmBdSoVSQS+WfLuRW1/xUoGr2DzBupTbv10jzjm4LY++t5D35n6T6XCcyxhPsC4tRhzdmT0b12LEU1P5fouXClzF5AnWpUW4ASEqFXirAldBlSjBSqolaQ8fVdYVZ/92jTj7oLY88t5C3p/npQJX8SSdYCVVkjRS0lJgPUV3yO3cj0YM6hRKBWOneanAVThxb5W9HPgceArwUxK3W7WqVWH0yT05dcz7jH5lFtce1y3TITlXZuIk2J8Br5jZkHQF48qnA9o35pyD2/LwuwsY1L0FB7ZvnOmQnCsTcWqwDYFn0xWIK99GDOpEm0bhBgQvFbiKIk6C/QzIS1cgrnyrVa0Ko4f1ZOE33zP6Fe+6wlUMcRLsdcCFkvZIVzCJJFWW9ImkF6L5dpI+kDRb0hOSqpVFHC51DkwoFXzgrQpcBRCnBtsbWAjMkPQMocXAtgLbmJndkKLYfgfMBOpF87cCd5rZ45LuB84D7kvRe7kyMmJQJyZ8sYIRT03j5d/1pVY179bQlV9J9wcraXsSm5mZVS5dSCCpNfAIcBNwKXAssBJoYWZbJR0EXGtmRxe3H+8PNju9N/cbTn/wfc49pC3XHOutClzuSbY/2DinD+1KEU9cdwEjgLrRfGNgjZnlXx1ZArQq7IWSLgAuAGjTxu97yEYH7dWYsw/ak4ffXcDg7nns365RpkNyLi2SrsGa2cJkptIGJGkosMLMpiQuLiykIuIcY2Z9zKxP06ZNSxuOS5MRgzrTumFNRoydysYtBStNzpUP2dgXwSHAcZIWAI8DRxDOaBtIyj/jbg18lZnwXCrUrl6F0Sf3YsE333Pbq96qwJVPsa4wRAnuBOAAQrvYggnazOy80gRkZlcCV0bv1x+43Mx+KulJYBgh6Z6Nt8nNeQft1ZizDtqTh96dz+AeLfhJWy8VuPIl6QQrqRHwBtCd8JPd2PHT3RKWlSrBFuMK4HFJNwKfAH9P0/u4MnTFoM68MWsFw5+cysu/60fNaqW+Rupc1ohTIrgR6Az8AtiLkFCPBroAjwEfES5GpYyZTTSzodHzeWa2v5l1MLNTzGxzKt/LZUbt6lW49eSeLPjme25/zUsFrnyJk2CPAR41s4eAddGybWY2y8x+BmwERqU6QFf+HbxXE848cE/+8c58Ji9YnelwnEuZOAm2BeEsFSC/uVSNhPX/A45LRVCu4hk5uDOtGtRk+Nhp3qrAlRtxEuxqoHb0fD3wA5B42+wPhAtfzsUWWhX0ZP6qDdzhpQJXTsRJsF8CXQHMbDvhQtM5kqpLqgWcBcxLfYiuoji4QxN+dmAb/u6lAldOxEmwrwHDJFWP5v9EaK61GlgB9AHuTG14rqK5cnCXH0sFm37wUoHLbXH0sx/NAAAZi0lEQVQS7M2EvgA2A5jZfwntUl8FXgbOMDNvOuVKxUsFrjxJuh2shV5hNhdY9jTwdKqDchXbwR2a8NMD2vC3t+czqHsLeu/pNyC43FTSUWWrS2rlfbK6dLlySBda1q/J8Ce9VOByV6wEK2k/SRMIrQgWAYdGy5tJGi9pYBpidBVQnephBIR5qzbwp3FfZjoc50okzrDd+wBvEe7iejRxnZmtAGoS+ghwLiUO6dCEMw5ow4NvzWPKwm8zHY5zscU5g72e0INVN2Aku3YhOB7YP0VxOQfAVfmlgrFTvVTgck6cBNsXeNDMvqPwvlgXAS1TEpVzkTpRXwXzVm7gTi8VuBwTJ8HWANYWs75eMeucK7FDO+4oFXy8yEsFLnfESbBzCQMfFuUIYEbpwnGucFcO7kxe/Zpc/qSXClzuiJNg/wOcWaClgAFIugwYBPwzhbE596O6Napyy8k9vFTgckqcBHs78D7hzq1JhOR6p6SlwGhgHHBvyiN0LtK3Y1NO399LBS53xBn0cAtwJHA5oe/XTcDewCrCCLBDo05gnEubq4Z0pkW9Ggz3UoHLAbFuNDCzrWZ2ZzRqa20zq2VmvczsjoQhtZ1Lm1Aq6MnclRu483UvFbjslo2jyjpXrH57N+X0/ffgwUnz+MRLBS6LFdnZi6SzSrJDM3t091s5VzpXDenCm7NWMnzsNF74zaHUqOqDJbrsU1xvWg+z88ixsPMNBipkGRS4jda5dMgvFZz1jw+56/XZjBzcOdMhObeL4hLs4QXmqwK3EkaOvZ/Q5lWEUQ5+SbjYdUUaYnSuUP32bsppP9mDMZPmMqh7C/bZo0GmQ3JuJ0XWYM3szcSJcKtsDaCHmd1iZs+Z2bNmNgroCdSKtnGuzFx1TBeae6sCl6XiXOQ6F3jIzNYXXGFm64CHom2cKzP1olLB7BXfcff42ZkOx7mdxEmwTYHiriRUBpqVLhzn4jts76ac2mcPHnhzLlMXr8l0OM79KE6C/QI4X9IuQ3NLagScD8xMVWDOxXH10FAquPzJqWze6qUClx3iJNhrgXbALEm3SDpX0jmSbiUk3z0JfcY6V+bq1ajKqJN6hFLB614qcNkhzqCHz0oaBtxNuDU20RLgVDP7XyqDcy6O/p2a8f/6tOb+N+dydLcW9PJWBS7D4t4q+wzQFjgAOB04I3re1syeSnl0zsX0h6FdQ6uCsV4qcJkX+1ZZM9tuZh+Z2RNm9nj03Dt5cVmhXo2q3HxSD75c/h1/9lYFLsO8LwJX7hzeqRmn9G7N/W/OY9oSb1XgMqfIBCtpvqS5kqpG8/OSmOaWXejOFe0PQ7vStE51b1XgMqq4M9iFhIEM8/saWBQtK25alLZInYuhfs3QquDL5d/xl/FzMh2Oq6CKbEVgZv2Lm3cu2x3euRnDerfmvqhVQY/W9TMdkqtgvAbryrU/Du1KkzrVvFTgMsITrCvX6tesyi0n9WTW8vXcM8FLBa5sFdfh9oQS7M/MbEAp4nEu5fJLBfdODKWC7q28VODKRnF3crVn1860nctJfzymK2/NXsnlT07luYsPpVoV//Hm0q+4/mDbmlm7uFNpA5K0h6Q3JM2U9Lmk30XLG0kaJ2l29LhLpzPOFaV+rdCq4Iuv13PPBL8BwZWNbPwzvhW4zMy6AAcCv5bUFRgJjDezjsD4aN65pB3RuTkn79eav06cy/SlazMdjqsAkk6wktpJOraY9cdKalvagMxsmZl9HD1fT+gCsRVwPPBItNkjwAmlfS9X8fzf0K40rh1aFWzZ6nd4u/SKcwZ7E7v2opXoMuCG0oWzsyhh7wt8ADQ3s2UQkjDeubcrgZ1KBW94qwKXXnES7KHAq8Wsf40UjsklqQ7wFHBJNCRNsq+7QNJkSZNXrlyZqnBcOTKgS3NO2q8V974xx0sFLq3iJNhmwNfFrF8BNC9dOEHU/8FTwL/N7Olo8XJJedH6vOj9dmFmY8ysj5n1adq0aSrCceXQNUO70chLBS7N4iTYNcBexazvAOwyIGJckgT8HZhpZn9KWPUccHb0/Gzg2dK+l6u46teqys0nhlLBX71U4NIkToJ9izAmV4uCK6JlvwDeTkFMhwBnAkdI+jSahgC3AEdKmg0cGc07V2IDuzbnpH1b8dc35vD5V14qcKkns+TuJZC0D/A+8C1wB/Ap4UaEfQkXuBoCh5rZ5PSEGl+fPn1s8uSsCcdloTXfb+HIOyfRpE51nv31IX4DgkuKpClm1md32yX9bTKzT4FhhLu/RhMueL0WPa8MnJJNydW5ZDSoVY1RJ/Zg5rJ13DvRSwUutZIe9BDAzF6Q1AY4GugICJgFvGZmG9MQn3NpN7Brc07ctxX3TJjDkV2b062l91XgUiNWggWIEqmPHuvKlWuO7crbc1Zx+ZPTeO7iQ6ha2UsFrvT8W+QcoVRwc36p4A0f+cilRtJnsJLmJbGZmVlxTbmcy1pHdm3OCfu05C8TZnNk1+Z0bVkv0yG5HBfnDLawMbmWAtWAtoROWnxMLpfTrjm2Gw1qhRsQftjmNyC40onTiqC/mR1eYOprZq2BnwJ1gAvTFqlzZaBh7WrcfGJ3ZnipwKVASmqwZvYY4cLXHanYn3OZdFS3FhwflQpmfJV0NxjO7SKVF7k+BfqlcH/OZcy1Ualg+FgvFbiSS2WC3Qfwb6IrFxrWrsZNJ3bn86/Wcd9ELxW4konTiqCos9NGwEDgfODpIrZxLucc3a0Fx/Xa0aqgS563KnDxxLnRYCKFD4Ko6PF14DelDci5bHLdcd14d+4qho+dyjO/8hsQXDxxEuy5hSwzYDXwpZl9mZqQnMseDWtX48YTenDhv6Zw/8S5/GZAx0yH5HJI0gnWzB7Z/VbOlT+Durfg2F4t+fOE2RzZrTmdW3ipwCWnRL93JFWX1EpStVQH5Fw2uu64btSvWdVvQHCxxEqwkvaTNIEwcsEiwjhdSGomabykgWmI0bmMa1S7Gjee0J3pS9fxwJveqsAlJ86w3fsQRjXYC3g0cZ2ZrQBqsmNIF+fKnUHd8zi2V0vuHj+bWV+XenQkVwHEOYO9HvgK6AaMZEfrgXzjgf1TFJdzWem647pRr4aXClxy4iTYvsCDZvYdhTfXWgS0TElUzmWp/FLBZ0vXMmZSMh3MuYosToKtARQ3MpxfWnUVwuAeeQztmcddr3/ppQJXrDgJdi7Qu5j1RwAzSheOc7khv1QwfOxUtnqpwBUhToL9D3BmgZYCBiDpMmAQ8M8UxuZc1mpcpzo3nNCdaUvW8oCXClwR4iTY2wnDdr8KTCIk1zslLSWMLDsOuDflETqXpYb0yOOYnnnc/fpsvlzupQK3qzgdbm8BjgQuBzYCm4C9gVXACGComflvJVehXH9cN+rWqMLlT3qpwO0q1o0GZrbVzO40sz5mVtvMaplZLzO7w8y2pitI57JVYqlgzFteKnA7866BnCulIT3yOKZHHneNm81sLxW4BJ5gnUuB647vRh0vFbgCPME6lwJN6lTnhuO7M3XJWh58a36mw3FZwhOscylyTM88hvRowZ3jvvRSgQM8wTqXUtcf3z2UCsZO81KB8wTrXCo1qVOd64/vxtTFa7xU4DzBOpdqx/TIY3B3LxU4T7DOpZwkbjihO7WrV/ZSQQXnCda5NAilgu5eKqjgPME6lyZDe3qpoKLzBOtcmnipwHmCdS6NvFRQsXmCdS7NvFRQcXmCdS7NJHH98V4qqIhyKsFKGiRplqQ5kkZmOh7nktW0rpcKKqKcSbCSKgN/BQYDXYHTJXXNbFTOJW9ozzwGdQulAh8ssWKokukAYtgfmGNm8wAkPQ4cjw+06HKEJG48sTuD7prE8X99m0sG7k3zetUxg2pVKiGEBGZh+0oK4zIJkH7cC5a/wU7Lw7r810vhdSVhu9+k+NfH2kFJ3i3/yOzHeZX0YCOHdmhC7eqpT4e5lGBbAYsT5pcABxTcSNIFwAUAbdq0KZvInEtSkzrVuf2UXvz84Y+45eUvMh2Oi7xxeX/aVfAEW9jfqF3+/JnZGGAMQJ8+fUr7x9i5lOvfqRlTrzmKbduNFes3U7mS2LrNsOjrrOirvt1spzPa/GWVK4X1icvzn+fvI95Z5K4Szwjzz4hjvT7G+XOcfZuFY8zfvxQ+k9Jq2aBGqfdRmFxKsEuAPRLmWwNfZSgW50qlbo2qADSoVS3Dkbh0ypmLXMBHQEdJ7SRVA04DnstwTM45V6ScOYM1s62SLgZeBSoD/zCzzzMclnPOFSlnEiyAmb0EvJTpOJxzLhm5VCJwzrmc4gnWOefSxBOsc86liSdY55xLE0+wzjmXJp5gnXMuTTzBOudcmshScB9vtpK0ElgY82VNgFVpCKeslZfjAD+WbFVejqUkx7GnmTXd3UblOsGWhKTJZtYn03GUVnk5DvBjyVbl5VjSeRxeInDOuTTxBOucc2niCXZXYzIdQIqUl+MAP5ZsVV6OJW3H4TVY55xLEz+Ddc65NPEEG8mFIcEl/UPSCknTE5Y1kjRO0uzosWG0XJL+HB3PNEn7Jbzm7Gj72ZLOzsBx7CHpDUkzJX0u6Xc5fCw1JH0oaWp0LNdFy9tJ+iCK64mok3gkVY/m50Tr2ybs68po+SxJR5f1sSTEUVnSJ5JeiOZz8lgkLZD0maRPJU2OlpXtd8zMKvxE6MB7LtAeqAZMBbpmOq5C4uwH7AdMT1g2GhgZPR8J3Bo9HwK8TBjL7EDgg2h5I2Be9Ngwet6wjI8jD9gvel4X+JIwFHsuHouAOtHzqsAHUYz/BU6Llt8PXBQ9/xVwf/T8NOCJ6HnX6HtXHWgXfR8rZ+h7dinwH+CFaD4njwVYADQpsKxMv2Nl/o+XjRNwEPBqwvyVwJWZjquIWNsWSLCzgLzoeR4wK3r+AHB6we2A04EHEpbvtF2GjulZ4MhcPxagFvAxYbTjVUCVgt8vwogcB0XPq0TbqeB3LnG7Mj6G1sB44AjghSi2XD2WwhJsmX7HvEQQFDYkeKsMxRJXczNbBhA9NouWF3VMWXWs0c/KfQlnfjl5LNFP6k+BFcA4whnbGjPbWkhcP8YcrV8LNCZLjgW4CxgBbI/mG5O7x2LAa5KmSLogWlam37GcGjImjZIaEjzHFHVMWXOskuoATwGXmNk6FT1+c1Yfi5ltA/aR1AB4BuhS2GbRY9Yei6ShwAozmyKpf/7iQjbN+mOJHGJmX0lqBoyT9EUx26blWPwMNsjlIcGXS8oDiB5XRMuLOqasOFZJVQnJ9d9m9nS0OCePJZ+ZrQEmEmp4DSTln8AkxvVjzNH6+sBqsuNYDgGOk7QAeJxQJriL3DwWzOyr6HEF4Q/f/pTxd8wTbJDLQ4I/B+Rf2TybUM/MX35WdHX0QGBt9JPoVeAoSQ2jK6hHRcvKjMKp6t+BmWb2p4RVuXgsTaMzVyTVBAYCM4E3gGHRZgWPJf8YhwETLBT3ngNOi67MtwM6Ah+WzVEEZnalmbU2s7aE/wMTzOyn5OCxSKotqW7+c8J3Yzpl/R0r68Jztk6Eq4hfEupnV2c6niJifAxYBvxA+Mt6HqHmNR6YHT02irYV8NfoeD4D+iTs5+fAnGg6NwPHcSjhZ9Y04NNoGpKjx9IT+CQ6lunA/0XL2xOSyhzgSaB6tLxGND8nWt8+YV9XR8c4Cxic4e9af3a0Isi5Y4linhpNn+f/ny7r75jfyeWcc2niJQLnnEsTT7DOOZcmnmCdcy5NPME651yaeIJ1zrk08QRbAUnaR9J4Sd9KMknXZkFME6MG7iV9ff/oWM5JXVQuWaX99yuv/FbZLCDpOULbwqOj+ZeBjWZ2UhreqwrhDqqqwB+BNYQ2nEVt35/QJvIuC3cqOeeS5Ak2OxwI3AMgqRKhx6Ib0/Re7aPpMjO7J4nt+wPXAA8TknG6HEXh930naxJQk3AThnNZwRNshknaG2gKvBMt6kG4p/vdNL1li+hxdTp2HvUxUNnMNsV5nZltKc37mtl2INZ7OpduXoPNAEl1JDWR1IRw7/p2YG40fySwFVgYbVM/yX22lfRPScslbZY0V9LNkmolbDMReDOafSiqWVpiT/QF9vkw4ewVYH7C9tdG66+N5rtJ+pOkJYQkd2C0/lRJz0laFMW0StL/JPUs5L12qeHlL5PUUtJjUc14g6RXoz9MidvuUoNNXCbpXIURBzZLWihpRBHHfJFCL/ybJH0p6eLo9aYdPUwVS1LH6N9imaQt0THcFt0Tn7/NHpK+Uehxv2aB1/9b0nZJAxOWxfksF0SfXS9Jr0v6TmEkjNslVVEYheF2SUuj45wkqUuBfeQf88Do33lh9L7TJJ2WzOeQ7GeR8Hn8I+F9Vkh6VxkYpSKV/Aw2M+5hR4cT+eYXmF8SPb5J+JleJEl7Eu4Frw/cR+hToT+h4+NDJA2w0F/nTYQz5asII2m+Fe1iZRG7fgCoB5wI/J7QoTLsWrP9N7ARuIPQx8CyaPnFhDPlMcDXwF7ABcA7kvYzs9nFHVekNuHn//tR3O2A3wHPSupuoavA3bkQaE7oYGYN8DPgVklLzOw/+RtJugK4hdBp9lWEDrSHU/TnswtJvYEJ0fs8ACwFegG/JfxbHGZmP5jZYknnEjobuQv4ZfT6nwNnALeY2esJu477WbYm9E37BDCWUIK5DNgGdCOUU24BmgCXA/+T1CX6JZDoVsK/wX2Ef9tzgcck1TCzh1PxWShcFxhH6Gf1XsL3tz6hn4e+wCPFvU9Wy2SHEhV1IgypMTCavgX+mTD/HfBgwnzvJPb3b8KXf0iB5bdFy89LWNY/WnZOkrFeG23ftph1E4l6vC+wvnYhy7oAm4F7CyyfCCwoZJkBIwosHx4tP7q440pY9hXQIGF5LULSfC9hWSPCH4lpQI2E5S0IHUkb0D+Jz2sq8AVQt8DyEwv73IE/R8uHAZ2jf//3Cn6eMT/LBdE+TymwfArh19KzRCNKR8t/W8jneU60bCFQP2F5/WjZaqDmbv79kvosCIl0l3/n8jB5iSADzGyGhbOTxUAD4JFofgXhbOEhM3s9mqYUty+Fi2LHAZ+Y2UsFVo8i/Ic6MeUHsbO7bEeP9z8ysw1RjJJUT6EEspLQw9IBSe57OyEJJZoQPXZMch8PWUILCDP7nnBGnPj6Iwm9Q91nCfVjM/ua8AdstyT1ICSL/wDVFZWBouN+G9hAOJNMNJzQG9eDhDPNrcAZBT/PEnyWS83syQLL3iZcSPyLRZktkv9LprDP8z4zW5sQx1rCuFwNKeaXVczPIn//hyt0jl1ueIItY9q5/noC4QxkZjR/LOGLNzfapk4Su2wK1CF0ybYTM1tN+LnePmUHULgvC1soaV+FkUnXE/4TrYymHoT/oMn4yna9YPZN9Ng4yX3MK2TZNwVe3y56nFXItoUtK0x+HfM6dhxr/pT/x7N54gvMbDNh3Ke6hJ/uvzKzguWiknyWu+yD8GupsHX5ywv7PGcWsmxG9Fjc9yrpz8LMFhLKV0cByxSGeBkt6SfF7D8neA227BVWf11SYP7r6PERwk+14pSmaVOqfF9wgaQ2hNrpOuAGQpLaQPgpeBfhj0IyiquxJnvsydRpU/E55u/jDuCVIrb5tpBlxxBGNoYwPtl/EleW8LMs7piLWpfs8CjJfFaxPgsz+4OkfxA+i77AL4Dhkkab2RVJvF9W8gRb9kYD/4qeP0tIok8T/oO9QCjyPx+tT2ZoihWEs5puBVco9MCeR+jQuqRK2mHwiYT/+MeZ2RsF4mpMOHPPJvlndZ3YUYIgYVky8i80bbOdL1AVKboQNIpwkWcVcJmkcWb2WsJmmfwsu7Lr6B75Z6eF/TLIF/uzMLN5wF+Av0iqQRg5YISkOywM+5JzvERQxhLqr18RLrb8O5pfTfiD92hC/XVGcfuK9redkJD3lTSowOqRhH/jZ0oR8nfRY6OYr8s/S9rpbEfS+exoi5tNxhES1UXRf24AJLUAfprkPj4hjGpwoaRdfj5HTaQaJczXIYx9tQY4k9CSYD7waIFaZCY/y4uU0FQwen4hIeY3i3xVjM9CUn2F9tM/ispC+eWJZMtJWcfPYDPnMMJV64+i+X6En4AlOdu8inCR5n+S7iUMbdEPOJXw07I0zVzejx5vlfRvQjvX6WY2fTeve5lQOvinpHsIPwcPIQwNM5cs++6Z2TeSrgNuJjR9+hfhD+AFhBpzH3ZzNm9mJulMwhnwtOgn7+fRfjoAJxGazj0cveQ+QnOrQWa2HCBqY/oO8IikIdHFqEx+lquAD6JjEaGZVhvgF9HFwkLF/CwOB8ZIeopQ/vgO6E0oE3xgZsnWwLNOVn3JK5jDCF+e/DuY+gHvWnLtOndiZgslHQBcT2jj2YBQ1x0F3FjYFf4Y+34nah96IeFKdxXChYtiE6yZzZU0mJCwriKchb1DOO57gLYljSldzGyUpHWEdra3AIsITd1ESLAbk9jHp5L2JSSP4wif23pC06mHCeNAIekswr/V6MRygJl9JOlqQinpUuCODH+WVxBqohcTLkrNBn5qCe2Hi5LsZ0FozvU0oVXCTwnlskWE470jZUeSAT4ml3O7IekvhATT0sJIo+Wewh1xDwGHm9nEzEaTu7wG61wksfaasCwPOItQFqkQydWljpcInNuhv6TbCD9XlxB+ep9PuII/MoNxuRzlCda5HeYQLhqdT2h0vwmYDIxKtqmRc4m8Buucc2niNVjnnEsTT7DOOZcmnmCdcy5NPME651yaeIJ1zrk08QTrnHNp8v8Bb1gEHjyc/NIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = loss\n",
    "x = list(range(1,len(loss)+1))\n",
    "plt.figure(figsize=(5,5))\n",
    "plt.plot(x, y)\n",
    "plt.xlabel(\"# of training examples\",fontsize=18)\n",
    "plt.ylabel(\"euclidean distance loss\",fontsize=18)\n",
    "plt.title(\"Level 1 Loss\",fontsize=18)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.spatial.distance import euclidean\n",
    "\n",
    "from sklearn.metrics.pairwise import euclidean_distances\n",
    "\n",
    "test_set =  lat_lng[10000:15000]\n",
    "predicted_val =[]\n",
    "for i,each_traj in enumerate(test_set):\n",
    "    x_test = each_traj[:len(each_traj) -1]\n",
    "    x_test = np.array(x_test).reshape(1, len(x_test), 2)\n",
    "    y_test = each_traj[-1]\n",
    "    y_test = np.array(y_test).reshape(1,2)\n",
    "    y_pred = model.predict(x_test)\n",
    "    predicted_val.append(y_pred.tolist()[0])\n",
    "        \n",
    "new_predicted_val = []\n",
    "for sublst in predicted_val:\n",
    "    for i, val in enumerate(sublst):\n",
    "        sublst[i] = round(val, 7)\n",
    "    new_predicted_val.append(sublst)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test Error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test error 0.002936369221322621\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.metrics.pairwise import euclidean_distances\n",
    "error = []\n",
    "for each_traj,y_pred in zip(test_set,new_predicted_val):\n",
    "    y_test = each_traj[-1]\n",
    "    error.extend(euclidean_distances([y_test],[y_pred]))\n",
    "        \n",
    "print(\"test error\",np.mean(error))   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example plot Predicted vs True Trajectory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "  <tr>\n",
    "    <td> <img src=\"http://drive.google.com/uc?export=view&id=1teJRtYL5_Y5La59JhD5K1Ye7OsIzfZie\" alt=\"Drawing\" style=\"width: 500px;\"/> </td>\n",
    "    <td> <img src=\"http://drive.google.com/uc?export=view&id=1Ykh3sqvj6ly9uTznqQa8BtpV-jwVr2Uw\" alt=\"Drawing\" style=\"width: 500px;\"/> </td>\n",
    "    </tr>\n",
    "    \n",
    "    \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Centroids from K- Means models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "centroids = [[1.2901505322971618, 103.85151526415854],\n",
    " [1.290761314882777, 103.85183701616937],\n",
    " [1.2898866212491749, 103.85139324211389],\n",
    " [1.2903683538500839, 103.85163185742208],\n",
    " [1.2908584102736864, 103.8519792337393],\n",
    " [1.290061721528241, 103.85165098408669],\n",
    " [1.290055102350767, 103.85144672301637],\n",
    " [1.2906218405153758, 103.85173958428693],\n",
    " [1.2897596030983194, 103.85130943752183],\n",
    " [1.2902503772023322, 103.85156459994279]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate Visitors near each Cluster - Using True Label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import euclidean_distances\n",
    "from collections import Counter\n",
    "calc_cluster = []\n",
    "for each_traj in lat_lng[10000:15000]:\n",
    "    label = each_traj[-1]\n",
    "    label = np.array(label).reshape(1,2)   \n",
    "    local_cluster = []\n",
    "    for center in centroids:\n",
    "        #print(float(euclidean_distances(label.tolist(), [center])[0][0]))\n",
    "        local_cluster.append(euclidean_distances(label.tolist(), [center])[0][0]) \n",
    "    calc_cluster.append(np.argmin(local_cluster))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({4: 2059,\n",
       "         3: 737,\n",
       "         9: 238,\n",
       "         6: 646,\n",
       "         7: 556,\n",
       "         8: 290,\n",
       "         1: 336,\n",
       "         0: 84,\n",
       "         2: 54})"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counter(calc_cluster)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate Visitors near each Cluster - Using Predicted Label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import euclidean_distances\n",
    "from collections import Counter\n",
    "calc_cluster = []\n",
    "for each_traj in new_predicted_val:\n",
    "    label = each_traj\n",
    "    label = np.array(label).reshape(1,2)   \n",
    "    local_cluster = []\n",
    "    for center in centroids:\n",
    "        #print(float(euclidean_distances(label.tolist(), [center])[0][0]))\n",
    "        local_cluster.append(euclidean_distances(label.tolist(), [center])[0][0]) \n",
    "    calc_cluster.append(np.argmin(local_cluster))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({1: 355,\n",
       "         6: 750,\n",
       "         3: 836,\n",
       "         4: 1762,\n",
       "         9: 306,\n",
       "         7: 637,\n",
       "         0: 94,\n",
       "         8: 227,\n",
       "         2: 32,\n",
       "         5: 1})"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counter(calc_cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def np_haversine(latlon1, latlon2):\n",
    "#     \"\"\"\n",
    "#     Numpy version of the Haversine function to calculate distances between two sets of points.\n",
    "#     Returns the distance in miles.\n",
    "#     \"\"\"\n",
    "#     lat1 = latlon1[:, 0]\n",
    "#     lon1 = latlon1[:, 1]\n",
    "#     lat2 = latlon2[:, 0]\n",
    "#     lon2 = latlon2[:, 1]\n",
    "    \n",
    "#     REarth = 3961\n",
    "#     lat = np.abs(lat1 - lat2) * np.pi / 180\n",
    "#     lon = np.abs(lon1 - lon2) * np.pi / 180\n",
    "#     lat1 = lat1 * np.pi / 180\n",
    "#     lat2 = lat2 * np.pi / 180\n",
    "#     a = np.sin(lat / 2) * np.sin(lat / 2) + np.cos(lat1) * np.cos(lat2) * np.sin(lon / 2) * np.sin(lon / 2)\n",
    "#     d = 2 * np.arctan2(np.sqrt(a), np.sqrt(1 - a))\n",
    "#     return REarth * d"
   ]
  }
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