nested-eutoencoder-keras.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.layers import Input, Dense, Reshape, TimeDistributed\n",
    "from keras.models import Model\n",
    "from keras.utils import plot_model\n",
    "from IPython.display import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "'''small encoder model'''\n",
    "small_enc_input = Input(shape=(12,), name='small_encoder_input')\n",
    "small_enc = Dense(2, name='bar_latent_space')(small_enc_input)\n",
    "small_encoder = Model(small_enc_input, small_enc, name='small_encoder')\n",
    "\n",
    "'''small decoder model'''\n",
    "small_dec_input = Input(shape=(2,), name='small_decoder_input')\n",
    "small_dec = Dense(12, name='bar_output')(small_dec_input)\n",
    "small_decoder = Model(small_dec_input, small_dec, name='small_decoder')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''small autoencoder model''' #It can be trained sepparetly\n",
    "small_enc_input = Input(shape=(12,), name='small_autoencoder_input')\n",
    "small_autoencoder_1 = small_encoder(small_enc_input)\n",
    "small_autoencoder_2 = small_decoder(small_autoencoder_1)\n",
    "small_autoencoder = Model(small_enc_input, small_autoencoder_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_model(small_autoencoder, to_file='model_plot.png', show_shapes=True, show_layer_names=True)\n",
    "Image('model_plot.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''nested autoenoder model'''\n",
    "enc_input = Input(shape=(4,12,), name='enc_input')\n",
    "small_encoder_output = TimeDistributed(small_encoder, input_shape=(12,), name='wraped_1')(enc_input)\n",
    "encoder_input = Reshape((8,))(small_encoder_output)\n",
    "encoder = Dense(2)(encoder_input)\n",
    "decoder = Dense(8)(encoder)\n",
    "small_decoder_input = Reshape((4,2))(decoder)\n",
    "small_decoder_output = TimeDistributed(small_decoder, input_shape=(2,), name='wraped_2')(small_decoder_input)\n",
    "\n",
    "\n",
    "encoder_model = Model(enc_input, small_decoder_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_model(encoder_model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)\n",
    "Image('model_plot.png')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}