{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy \n",
    "import numpy as np\n",
    "from keras.models import Model\n",
    "from keras.layers import Dense, Merge, concatenate, Input\n",
    "from keras.layers import LSTM\n",
    "from keras.utils import np_utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "inp1 = Input(shape=(10,20))\n",
    "inp2 = Input(shape=(10,32))\n",
    "cc1 = concatenate([inp1, inp2],axis=2) # Merge column, same row\n",
    "output = Dense(30, activation='relu')(cc1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Model(inputs=[inp1, inp2], outputs=output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_40 (InputLayer)           (None, 10, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "input_41 (InputLayer)           (None, 10, 32)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_21 (Concatenate)    (None, 10, 52)       0           input_40[0][0]                   \n",
      "                                                                 input_41[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "dense_12 (Dense)                (None, 10, 30)       1590        concatenate_21[0][0]             \n",
      "==================================================================================================\n",
      "Total params: 1,590\n",
      "Trainable params: 1,590\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_42 (InputLayer)           (None, 20, 10)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "input_43 (InputLayer)           (None, 32, 10)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_22 (Concatenate)    (None, 52, 10)       0           input_42[0][0]                   \n",
      "                                                                 input_43[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "dense_13 (Dense)                (None, 52, 30)       330         concatenate_22[0][0]             \n",
      "==================================================================================================\n",
      "Total params: 330\n",
      "Trainable params: 330\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "inp1 = Input(shape=(20,10))\n",
    "inp2 = Input(shape=(32,10))\n",
    "cc1 = concatenate([inp1, inp2],axis=1) # Merge row, same column\n",
    "output = Dense(30, activation='relu')(cc1)\n",
    "model = Model(inputs=[inp1, inp2], outputs=output)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_44 (InputLayer)           (None, 10, 10)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "input_45 (InputLayer)           (None, 10, 10)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_23 (Concatenate)    (None, 10, 10)       0           input_44[0][0]                   \n",
      "                                                                 input_45[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "dense_14 (Dense)                (None, 10, 30)       330         concatenate_23[0][0]             \n",
      "==================================================================================================\n",
      "Total params: 330\n",
      "Trainable params: 330\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "inp1 = Input(shape=(10,10))\n",
    "inp2 = Input(shape=(10,10))\n",
    "cc1 = concatenate([inp1, inp2],axis=0) # Merge data must same row column\n",
    "output = Dense(30, activation='relu')(cc1)\n",
    "model = Model(inputs=[inp1, inp2], outputs=output)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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