CNN_Generated_Images_keras_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from __future__ import print_function\n",
    "import numpy as np\n",
    "import scipy.io as sio\n",
    "import pandas as pd\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "np.random.seed(1337)  # for reproducibility\n",
    "\n",
    "# from keras.datasets import mnist\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout, Activation, Flatten\n",
    "from keras.layers.normalization import BatchNormalization\n",
    "from keras.layers import Convolution2D, MaxPooling2D, AveragePooling2D\n",
    "from keras.utils import np_utils\n",
    "from keras import backend as K\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# input image dimensions\n",
    "img_rows, img_cols = 128, 128\n",
    "# size of pooling area for max pooling\n",
    "pool_size = (2, 2)\n",
    "# convolution kernel size\n",
    "kernel_size = (3, 3)\n",
    "\n",
    "# Training data, shuffled and split\n",
    "WB = np.array(sio.loadmat('sandstone_data.mat')['Data'])\n",
    "Y_data = np.array(sio.loadmat('sandstone_data.mat')['L'])\n",
    "# Y_data = (Y_data-min(Y_data))/(max(Y_data)-min(Y_data))\n",
    "X_data = np.reshape(WB,(768,1,img_rows,img_cols))\n",
    "\n",
    "\n",
    "# Add 380 generated images using VAE+ST from Ruijin's code\n",
    "WB_gen = np.array(sio.loadmat('generate_sandstone_data_noshuffle.mat')['sample_total'])\n",
    "Y_gen = np.array(sio.loadmat('generate_sandstone_data_noshuffle.mat')['Data_all'])[:,-1]\n",
    "X_gen = np.transpose(np.reshape(WB_gen,(380,1,img_rows,img_cols)),[0,1,3,2])\n",
    "\n",
    "# Test Data\n",
    "WB1 = sio.loadmat('test_sandstone_data.mat')['Data']\n",
    "X_test = np.reshape(WB1, (240, 1, img_rows, img_cols))\n",
    "Y_test = sio.loadmat('test_sandstone_data.mat')['L']\n",
    "\n",
    "index = np.random.permutation(len(X_gen))\n",
    "X_gen = X_gen[index]\n",
    "Y_gen = Y_gen[index]\n",
    "\n",
    "#Define Traing data and validation data\n",
    "X_total = np.concatenate((X_data, X_gen, X_test))\n",
    "Y_total = np.concatenate((Y_data.reshape(-1), Y_gen.reshape(-1),Y_test.reshape(-1)),axis=0)\n",
    "Y_total = (Y_total-min(Y_total))/(max(Y_total)-min(Y_total))\n",
    "\n",
    "# X_train = np.concatenate((X_data[0:700], X_gen[0:150], X_gen[230:380]), axis=0);\n",
    "# Y_train = np.concatenate((Y_data[0:700], Y_gen[0:150], Y_gen[230:380]), axis=0);\n",
    "# X_val = np.concatenate((X_data[700:768], X_gen[150:230]), axis=0);\n",
    "# Y_val = np.concatenate((Y_data[700:768], Y_gen[150:230]), axis=0);\n",
    "                         \n",
    "X_train = X_total[:1000]                  \n",
    "Y_train = Y_total[:1000]\n",
    "\n",
    "X_val = X_total[1000:-240]\n",
    "Y_val = Y_total[1000:-240]\n",
    "\n",
    "X_test = X_total[-240:]                  \n",
    "Y_test = Y_total[-240:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train shape: (1000, 128, 128, 1)\n",
      "1000 train samples\n",
      "148 validate samples\n",
      "240 test samples\n"
     ]
    }
   ],
   "source": [
    "if K.image_dim_ordering() == 'th':\n",
    "    X_train = X_train.reshape(X_train.shape[0], 1, img_rows, img_cols)\n",
    "    X_val = X_val.reshape(X_val.shape[0], 1, img_rows, img_cols)\n",
    "    X_test = X_test.reshape(X_test.shape[0], 1, img_rows, img_cols)\n",
    "    input_shape = (1, img_rows, img_cols)\n",
    "else:\n",
    "    X_train = X_train.reshape(X_train.shape[0], img_rows, img_cols, 1)\n",
    "    X_val = X_val.reshape(X_val.shape[0], img_rows, img_cols, 1)\n",
    "    X_test = X_test.reshape(X_test.shape[0], img_rows, img_cols, 1)\n",
    "    input_shape = (img_rows, img_cols, 1)\n",
    "    \n",
    "\n",
    "X_train = X_train.astype('float32')\n",
    "X_val = X_val.astype('float32')\n",
    "X_test = X_test.astype('float32')\n",
    "\n",
    "print('X_train shape:', X_train.shape)\n",
    "print(X_train.shape[0], 'train samples')\n",
    "print(X_val.shape[0], 'validate samples')\n",
    "print(X_test.shape[0], 'test samples')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# CNN\n",
    "\n",
    "model = Sequential()\n",
    "\n",
    "model.add(Convolution2D(24, (6, 6), padding='same', input_shape=input_shape))\n",
    "# model.add(BatchNormalization(axis=3))\n",
    "model.add(Activation('relu'))\n",
    "model.add(MaxPooling2D(pool_size=pool_size))\n",
    "\n",
    "model.add(Convolution2D(48, (3, 3), padding='same'))\n",
    "# model.add(BatchNormalization(axis=3))\n",
    "model.add(Activation('relu'))\n",
    "model.add(MaxPooling2D(pool_size=pool_size))\n",
    "\n",
    "\n",
    "model.add(Convolution2D(96, (3, 3), padding='same'))\n",
    "# model.add(BatchNormalization(axis=3))\n",
    "model.add(Activation('relu'))\n",
    "model.add(MaxPooling2D(pool_size=pool_size))\n",
    "\n",
    "\n",
    "# model.add(Convolution2D(64, (3, 3), padding='same'))\n",
    "# model.add(BatchNormalization(axis=3))\n",
    "# model.add(Activation('relu'))\n",
    "# model.add(MaxPooling2D(pool_size=pool_size))\n",
    "\n",
    "\n",
    "# model.add(Convolution2D(128, (3, 3), padding='same'))\n",
    "# model.add(BatchNormalization(axis=3))\n",
    "# model.add(Activation('relu'))\n",
    "# model.add(MaxPooling2D(pool_size=pool_size))\n",
    "\n",
    "\n",
    "#Training result was worse with this layer...complex network led to overfitting...need to fine tune the framework\n",
    "model.add(Convolution2D(128, (3, 3), padding='same'))\n",
    "# model.add(BatchNormalization(axis=3))\n",
    "model.add(Activation('relu'))\n",
    "\n",
    "\n",
    "model.add(Flatten())\n",
    "model.add(Dense(1000))\n",
    "model.add(Dropout(0.25))\n",
    "model.add(Activation('relu'))\n",
    "model.add(Dense(100))\n",
    "model.add(Dropout(0.25))\n",
    "model.add(Activation('relu'))\n",
    "# model.add(Dropout(0.5))\n",
    "# model.add(Dense(10))\n",
    "# model.add(Activation('relu'))\n",
    "# model.add(Dropout(0.25))\n",
    "model.add(Dense(1))\n",
    "model.add(Activation('relu'))\n",
    "\n",
    "model.compile(loss='mse', optimizer='adam', metrics=['mae'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_23 (Conv2D)           (None, 128, 128, 24)      888       \n",
      "_________________________________________________________________\n",
      "activation_35 (Activation)   (None, 128, 128, 24)      0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_20 (MaxPooling (None, 64, 64, 24)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_24 (Conv2D)           (None, 64, 64, 48)        10416     \n",
      "_________________________________________________________________\n",
      "activation_36 (Activation)   (None, 64, 64, 48)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_21 (MaxPooling (None, 32, 32, 48)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_25 (Conv2D)           (None, 32, 32, 96)        41568     \n",
      "_________________________________________________________________\n",
      "activation_37 (Activation)   (None, 32, 32, 96)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_22 (MaxPooling (None, 16, 16, 96)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_26 (Conv2D)           (None, 16, 16, 128)       110720    \n",
      "_________________________________________________________________\n",
      "activation_38 (Activation)   (None, 16, 16, 128)       0         \n",
      "_________________________________________________________________\n",
      "flatten_6 (Flatten)          (None, 32768)             0         \n",
      "_________________________________________________________________\n",
      "dense_13 (Dense)             (None, 1000)              32769000  \n",
      "_________________________________________________________________\n",
      "dropout_8 (Dropout)          (None, 1000)              0         \n",
      "_________________________________________________________________\n",
      "activation_39 (Activation)   (None, 1000)              0         \n",
      "_________________________________________________________________\n",
      "dense_14 (Dense)             (None, 100)               100100    \n",
      "_________________________________________________________________\n",
      "dropout_9 (Dropout)          (None, 100)               0         \n",
      "_________________________________________________________________\n",
      "activation_40 (Activation)   (None, 100)               0         \n",
      "_________________________________________________________________\n",
      "dense_15 (Dense)             (None, 1)                 101       \n",
      "_________________________________________________________________\n",
      "activation_41 (Activation)   (None, 1)                 0         \n",
      "=================================================================\n",
      "Total params: 33,032,793\n",
      "Trainable params: 33,032,793\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 1000 samples, validate on 148 samples\n",
      "Epoch 1/1200\n",
      "1000/1000 [==============================] - 1s - loss: 1.4743 - mean_absolute_error: 0.4317 - val_loss: 0.0086 - val_mean_absolute_error: 0.0824\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 2/1200\n",
      "1000/1000 [==============================] - 1s - loss: 0.0248 - mean_absolute_error: 0.1275 - val_loss: 0.0084 - val_mean_absolute_error: 0.0835\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 3/1200\n",
      "1000/1000 [==============================] - 1s - loss: 0.0135 - mean_absolute_error: 0.0909 - val_loss: 0.0032 - val_mean_absolute_error: 0.0512\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 4/1200\n",
      "1000/1000 [==============================] - 1s - loss: 0.0079 - mean_absolute_error: 0.0652 - val_loss: 6.4625e-04 - val_mean_absolute_error: 0.0209\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 5/1200\n",
      "1000/1000 [==============================] - 1s - loss: 0.0053 - mean_absolute_error: 0.0519 - val_loss: 4.1673e-04 - val_mean_absolute_error: 0.0164\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 6/1200\n",
      "1000/1000 [==============================] - 1s - loss: 0.0054 - mean_absolute_error: 0.0528 - val_loss: 0.0011 - val_mean_absolute_error: 0.0287\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 7/1200\n",
      "1000/1000 [==============================] - 1s - loss: 0.0044 - mean_absolute_error: 0.0478 - val_loss: 0.0011 - val_mean_absolute_error: 0.0294\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 8/1200\n",
      "1000/1000 [==============================] - 1s - loss: 0.0058 - mean_absolute_error: 0.0547 - val_loss: 0.0014 - val_mean_absolute_error: 0.0335\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n",
      "Epoch 9/1200\n",
      " 600/1000 [=================>............] - ETA: 0s - loss: 0.0049 - mean_absolute_error: 0.0523\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-37-a40b81fd6ab7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# model.fit(X_train, Y_train, batch_size=40, epochs=1200, verbose=1, validation_data=(X_val, Y_val),\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;31m#           callbacks=[early_stop], initial_epoch=0)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m40\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1200\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidation_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_val\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_val\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/keras/models.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)\u001b[0m\n\u001b[1;32m    851\u001b[0m                               \u001b[0mclass_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mclass_weight\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    852\u001b[0m                               \u001b[0msample_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 853\u001b[0;31m                               initial_epoch=initial_epoch)\n\u001b[0m\u001b[1;32m    854\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    855\u001b[0m     def evaluate(self, x, y, batch_size=32, verbose=1,\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/keras/engine/training.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)\u001b[0m\n\u001b[1;32m   1484\u001b[0m                               \u001b[0mval_f\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mval_f\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval_ins\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mval_ins\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshuffle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshuffle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1485\u001b[0m                               \u001b[0mcallback_metrics\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallback_metrics\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1486\u001b[0;31m                               initial_epoch=initial_epoch)\n\u001b[0m\u001b[1;32m   1487\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1488\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mevaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/keras/engine/training.pyc\u001b[0m in \u001b[0;36m_fit_loop\u001b[0;34m(self, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch)\u001b[0m\n\u001b[1;32m   1139\u001b[0m                 \u001b[0mbatch_logs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'size'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch_ids\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1140\u001b[0m                 \u001b[0mcallbacks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_batch_begin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_logs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1141\u001b[0;31m                 \u001b[0mouts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mins_batch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1142\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mouts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1143\u001b[0m                     \u001b[0mouts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mouts\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/keras/backend/tensorflow_backend.pyc\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m   2101\u001b[0m         \u001b[0msession\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_session\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2102\u001b[0m         updated = session.run(self.outputs + [self.updates_op],\n\u001b[0;32m-> 2103\u001b[0;31m                               feed_dict=feed_dict)\n\u001b[0m\u001b[1;32m   2104\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mupdated\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2105\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m    765\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    766\u001b[0m       result = self._run(None, fetches, feed_dict, options_ptr,\n\u001b[0;32m--> 767\u001b[0;31m                          run_metadata_ptr)\n\u001b[0m\u001b[1;32m    768\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    769\u001b[0m         \u001b[0mproto_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc\u001b[0m in \u001b[0;36m_run\u001b[0;34m(self, handle, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m    963\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mfinal_fetches\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mfinal_targets\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    964\u001b[0m       results = self._do_run(handle, final_targets, final_fetches,\n\u001b[0;32m--> 965\u001b[0;31m                              feed_dict_string, options, run_metadata)\n\u001b[0m\u001b[1;32m    966\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    967\u001b[0m       \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc\u001b[0m in \u001b[0;36m_do_run\u001b[0;34m(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m   1013\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mhandle\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1014\u001b[0m       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,\n\u001b[0;32m-> 1015\u001b[0;31m                            target_list, options, run_metadata)\n\u001b[0m\u001b[1;32m   1016\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1017\u001b[0m       return self._do_call(_prun_fn, self._session, handle, feed_dict,\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc\u001b[0m in \u001b[0;36m_do_call\u001b[0;34m(self, fn, *args)\u001b[0m\n\u001b[1;32m   1020\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_do_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1021\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1022\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1023\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mOpError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1024\u001b[0m       \u001b[0mmessage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_text\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/p2admin/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc\u001b[0m in \u001b[0;36m_run_fn\u001b[0;34m(session, feed_dict, fetch_list, target_list, options, run_metadata)\u001b[0m\n\u001b[1;32m   1002\u001b[0m         return tf_session.TF_Run(session, options,\n\u001b[1;32m   1003\u001b[0m                                  \u001b[0mfeed_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfetch_list\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget_list\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1004\u001b[0;31m                                  status, run_metadata)\n\u001b[0m\u001b[1;32m   1005\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1006\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_prun_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msession\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhandle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeed_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfetch_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "from keras.callbacks import EarlyStopping\n",
    "early_stop = EarlyStopping(monitor='val_loss', min_delta=0, patience=0, verbose=0, mode='min')\n",
    "model.fit(X_train, Y_train, batch_size=40, epochs=1000, verbose=1, validation_data=(X_val, Y_val),\n",
    "          callbacks=[early_stop], initial_epoch=0)\n",
    "# model.fit(X_train, Y_train, batch_size=40, epochs=1200, verbose=1, validation_data=(X_val, Y_val))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training mse: 0.000906727082707\n",
      "testing mse: 0.00188723822854\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1gAAAI4CAYAAAB3HEhGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/WkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efecbd3fed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=[]\n",
    "num_comp=240\n",
    "for i in range(num_comp):\n",
    "    x.append(i)\n",
    "\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "ax1=fig.add_subplot(2,1,1)\n",
    "\n",
    "train_pred=model.predict(X_train)\n",
    "print('training mse:', mean_squared_error(Y_train, train_pred))\n",
    "\n",
    "ax1.plot(x,train_pred[0:num_comp], label='predict')\n",
    "ax1.plot(x,Y_train[0:num_comp],label='real')\n",
    "plt.legend()\n",
    "ax1.set_title('Prediction Result')\n",
    "ax1.set_xlabel('Image Number')\n",
    "ax1.set_ylabel('Normalized Modulus Coefficient')\n",
    "\n",
    "\n",
    "ax2=fig.add_subplot(2,1,2)\n",
    "\n",
    "test_pred=model.predict(X_test)\n",
    "print('testing mse:', mean_squared_error(Y_test, test_pred))\n",
    "\n",
    "ax2.plot(x,test_pred[0:num_comp], label='predict')\n",
    "ax2.plot(x,Y_test[0:num_comp],label='real')\n",
    "plt.legend()\n",
    "ax2.set_title('Prediction Result')\n",
    "ax2.set_xlabel('Image Number')\n",
    "ax2.set_ylabel('Normalized Modulus Coefficient')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7efe9a47db50>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD8CAYAAACMwORRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efecbd0c090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(Y_test.reshape(-1),test_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_1 (Conv2D)            (None, 128, 128, 24)      888       \n",
      "_________________________________________________________________\n",
      "batch_normalization_1 (Batch (None, 128, 128, 24)      96        \n",
      "_________________________________________________________________\n",
      "activation_1 (Activation)    (None, 128, 128, 24)      0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 64, 64, 24)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 64, 64, 32)        6944      \n",
      "_________________________________________________________________\n",
      "batch_normalization_2 (Batch (None, 64, 64, 32)        128       \n",
      "_________________________________________________________________\n",
      "activation_2 (Activation)    (None, 64, 64, 32)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2 (None, 32, 32, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 32, 32, 48)        13872     \n",
      "_________________________________________________________________\n",
      "batch_normalization_3 (Batch (None, 32, 32, 48)        192       \n",
      "_________________________________________________________________\n",
      "activation_3 (Activation)    (None, 32, 32, 48)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2 (None, 16, 16, 48)        0         \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 16, 16, 48)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_4 (Conv2D)            (None, 16, 16, 64)        27712     \n",
      "_________________________________________________________________\n",
      "batch_normalization_4 (Batch (None, 16, 16, 64)        256       \n",
      "_________________________________________________________________\n",
      "activation_4 (Activation)    (None, 16, 16, 64)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2 (None, 8, 8, 64)          0         \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 8, 8, 64)          0         \n",
      "_________________________________________________________________\n",
      "conv2d_5 (Conv2D)            (None, 8, 8, 128)         73856     \n",
      "_________________________________________________________________\n",
      "batch_normalization_5 (Batch (None, 8, 8, 128)         512       \n",
      "_________________________________________________________________\n",
      "activation_5 (Activation)    (None, 8, 8, 128)         0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_5 (MaxPooling2 (None, 4, 4, 128)         0         \n",
      "_________________________________________________________________\n",
      "dropout_3 (Dropout)          (None, 4, 4, 128)         0         \n",
      "_________________________________________________________________\n",
      "conv2d_6 (Conv2D)            (None, 4, 4, 128)         147584    \n",
      "_________________________________________________________________\n",
      "batch_normalization_6 (Batch (None, 4, 4, 128)         512       \n",
      "_________________________________________________________________\n",
      "activation_6 (Activation)    (None, 4, 4, 128)         0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_6 (MaxPooling2 (None, 2, 2, 128)         0         \n",
      "_________________________________________________________________\n",
      "dropout_4 (Dropout)          (None, 2, 2, 128)         0         \n",
      "_________________________________________________________________\n",
      "average_pooling2d_1 (Average (None, 1, 1, 128)         0         \n",
      "_________________________________________________________________\n",
      "flatten_1 (Flatten)          (None, 128)               0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 100)               12900     \n",
      "_________________________________________________________________\n",
      "activation_7 (Activation)    (None, 100)               0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 1)                 101       \n",
      "_________________________________________________________________\n",
      "activation_8 (Activation)    (None, 1)                 0         \n",
      "=================================================================\n",
      "Total params: 285,553\n",
      "Trainable params: 284,705\n",
      "Non-trainable params: 848\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.save('best_trained_CNN_generated_image_model_62117.h5')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}