Stacked_LSTM_+_VGG16.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Stacked LSTM + VGG16.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "mount_file_id": "1Dd3sQTq26bBfJfrbaONVR7PZ-V1O9jTn",
      "authorship_tag": "ABX9TyND0XTR3l/Up4LKfLacmWTw"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "JZ16OFcNWZD_"
      },
      "source": [
        "#Importing all the libraries needed\n",
        "import keras\n",
        "import h5py\n",
        "from keras import optimizers, preprocessing, Input\n",
        "from keras.models import load_model, Model\n",
        "from keras.layers import Bidirectional\n",
        "#from multimodel baseline functions\n",
        "from keras.layers.core import Reshape, Dropout\n",
        "from keras.utils.vis_utils import  plot_model\n",
        "import os\n",
        "import itertools\n",
        "#import keras matrics\n",
        "import matplotlib.pyplot as plt\n",
        "from keras.layers import Conv1D, MaxPooling1D, Flatten, GlobalAveragePooling3D\n",
        "from keras import regularizers\n",
        "import seaborn as sns\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from keras.applications.inception_v3 import InceptionV3\n",
        "\n",
        "import pandas as pd\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "import re\n",
        "from nltk.corpus import stopwords\n",
        "# from nltk import word_tokenize\n",
        "from keras.preprocessing import image\n",
        "from keras.applications.vgg16 import VGG16, preprocess_input\n",
        "from keras.preprocessing.text import Tokenizer\n",
        "import numpy as np\n",
        "from keras.layers import Dense, GlobalAveragePooling2D, Embedding, LSTM, multiply\n",
        "from PIL import Image, ImageFile"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mVZPGjc5slUg",
        "outputId": "682e387a-0cdd-4e8d-ecae-bdb9ebdd7f70"
      },
      "source": [
        "import nltk\n",
        "nltk.download('stopwords')\n",
        "STOPWORDS = set(stopwords.words('english'))\n",
        "REPLACE_BY_SPACE_RE = re.compile('[/(){}\\[\\]\\|@,;]')\n",
        "BAD_SYMBOLS = re.compile('[^0-9a-z #+_]')\n",
        "EMAIL = re.compile('^([a-zA-Z0-9_\\-\\.]+)@([a-zA-Z0-9_\\-\\.]+)\\.([a-zA-Z]{2,5})$')\n",
        "STOPWORDS = set(stopwords.words('english'))"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OBXeh_1MwAO5"
      },
      "source": [
        "#training_path, testing_path and validation_path are for the text extracted from the meme images respectively in a .csv file\n",
        "Training_path = '/content/drive/MyDrive/Code and Program/MultiOFF_Dataset/Split Dataset/Training_meme_dataset.csv'\n",
        "Testing_path = '/content/drive/MyDrive/Code and Program/MultiOFF_Dataset/Split Dataset/Testing_meme_dataset.csv'\n",
        "Validation_path = '/content/drive/MyDrive/Code and Program/MultiOFF_Dataset/Split Dataset/Validation_meme_dataset.csv'\n",
        "img_dir = '/content/drive/MyDrive/Code and Program/MultiOFF_Dataset/Labelled Images'"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8KzcJ3zryW7K"
      },
      "source": [
        "maxlen = 1000"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F1G270ZYYNjE"
      },
      "source": [
        "#directory for storing glove embeddings\n",
        "GLOVE_DIR = \"/content/drive/MyDrive/Code and Program/\"\n",
        "EMBEDDING_DIM = 50"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FKUGsNhAZCiv"
      },
      "source": [
        "#assigning weight\n",
        "class_weight = {1: 1.4,\n",
        "                0: 1}"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "10V6XSpUlKNb"
      },
      "source": [
        "#model with adam optimizer\n",
        "adam = keras.optimizers.Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0, amsgrad=False)\n",
        "sgd = optimizers.SGD(learning_rate=0.001, decay=1e-6, momentum=0.9, nesterov=True)\n",
        "adadelta = optimizers.Adadelta(learning_rate=1.0, rho=0.9, epsilon=None, decay=0.0)"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AnsOYcAvpTL8"
      },
      "source": [
        "def Image_model(base_model):\n",
        "  #freezing all the trainable layers\n",
        "  for layer in base_model.layers:\n",
        "    layer.trainable = False\n",
        "  #create output layer\n",
        "  x = base_model.output\n",
        "  #pooling layer before the output\n",
        "  x = GlobalAveragePooling2D()(x)\n",
        "  return x"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9-ohfHVFptWj"
      },
      "source": [
        "def read_data(file_name):\n",
        "  #Opening file\n",
        "    with open(file_name,'r', encoding=\"utf8\") as f:\n",
        "      #Creating empty set and dictonary for vocab and word respectively\n",
        "        word_vocab = set() \n",
        "        word2vector = {}\n",
        "        #Iterating over each line of file\n",
        "        for line in f:\n",
        "            #Spliting lines\n",
        "            line_ = line.strip() \n",
        "            #Splitting words\n",
        "            words_Vec = line_.split()            \n",
        "            word_vocab.add(words_Vec[0])\n",
        "            word2vector[words_Vec[0]] = np.array(words_Vec[1:],dtype=float)\n",
        "    print(\"Total Words in DataSet:\",len(word_vocab))\n",
        "    return word_vocab,word2vector"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0uMBlfACzWcB"
      },
      "source": [
        "def encode_label(DataFrame, Label_col):\n",
        "    t_y = DataFrame[Label_col].values\n",
        "    Encoder = LabelEncoder()\n",
        "    y = Encoder.fit_transform(t_y)\n",
        "    DataFrame[Label_col] = y"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-J1X-iKQ0WVT"
      },
      "source": [
        "def clean_text(text):\n",
        "   text = text.lower()\n",
        "   text = EMAIL.sub('', text)\n",
        "#     text = NUMBERS.sub('',text)\n",
        "   text = REPLACE_BY_SPACE_RE.sub(' ',text)\n",
        "   text = BAD_SYMBOLS.sub('',text)    \n",
        "   text = text.replace('x','')\n",
        "   text = ' '.join(word for word in text.split() if word not in STOPWORDS)\n",
        "    \n",
        "   return text"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qmDPpVEpykr0"
      },
      "source": [
        "def preprocess_text(Training_path,Validation_path, Testing_path):\n",
        "    # function to preprocess input\n",
        "    training_DF = pd.read_csv(Training_path, sep = ',')\n",
        "    validation_DF = pd.read_csv(Validation_path, sep = ',')\n",
        "    testing_DF = pd.read_csv(Testing_path, sep = ',')\n",
        "\n",
        "    # encoding all the labels \n",
        "    encode_label(testing_DF,'label')\n",
        "    encode_label(training_DF, 'label')\n",
        "    encode_label(validation_DF, 'label')\n",
        "\n",
        "    clean_text(training_DF['sentence'][0])\n",
        "\n",
        "    # Processing the text\n",
        "    training_DF['sentence'] = training_DF['sentence'].apply(clean_text)\n",
        "    testing_DF['sentence'] = testing_DF['sentence'].apply(clean_text)\n",
        "    validation_DF['sentence'] = validation_DF['sentence'].apply(clean_text)\n",
        "\n",
        "    return training_DF, testing_DF, validation_DF"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eqp1x84rqsy0"
      },
      "source": [
        "#splitting data into train, test and validation\n",
        "training_df, testing_df, validation_df = preprocess_text(Training_path,Validation_path, Testing_path)"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YSlvO5pcrGRl"
      },
      "source": [
        "def create_img_array(img_dirct):\n",
        "    all_imgs = []\n",
        "    for root, j, files in os.walk(img_dirct):\n",
        "        for file in files:\n",
        "            file = root + '/' + file\n",
        "            all_imgs.append(file)\n",
        "    return all_imgs\n",
        "\n",
        "def create_img_path(DF, Col_name, img_dir):\n",
        "    img_path = [img_dir + '/' + name for name in DF[Col_name]]\n",
        "    return img_path"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JCY4fP4p1--G"
      },
      "source": [
        "# Processing image and text for each set\n",
        "# Creating train, test and validation image path\n",
        "train_img_path = create_img_path(training_df,'image_name', img_dir)\n",
        "test_img_path = create_img_path(testing_df,'image_name', img_dir)\n",
        "val_img_path = create_img_path(validation_df,'image_name', img_dir)\n",
        "\n",
        "# Processing the text\n",
        "training_df['sentence'] = training_df['sentence'].apply(clean_text)\n",
        "testing_df['sentence'] = testing_df['sentence'].apply(clean_text)\n",
        "validation_df['sentence'] = validation_df['sentence'].apply(clean_text)"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TOqW1lLO2Dxc"
      },
      "source": [
        "# Vectorising text\n",
        "# process the whole observation into single list\n",
        "train_text_list=list(training_df['sentence'])\n",
        "test_text_list = list(testing_df['sentence'])\n",
        "val_text_list = list(validation_df['sentence'])\n",
        "\n",
        "# Creating vectors for train, test, validation\n",
        "tokenizer = Tokenizer(num_words=1000)\n",
        "tokenizer.fit_on_texts(train_text_list)\n",
        "sequences_train = tokenizer.texts_to_sequences(train_text_list)\n",
        "sequences_test = tokenizer.texts_to_sequences(test_text_list)\n",
        "sequences_val = tokenizer.texts_to_sequences(val_text_list)\n",
        "\n",
        "x_train = preprocessing.sequence.pad_sequences(sequences_train, maxlen=maxlen)\n",
        "x_test = preprocessing.sequence.pad_sequences(sequences_test, maxlen=maxlen)\n",
        "x_val = preprocessing.sequence.pad_sequences(sequences_val, maxlen=maxlen)\n",
        "\n",
        "# encoding all the labels \n",
        "y_test = testing_df['label']\n",
        "y_train = training_df['label']\n",
        "y_val = validation_df['label']"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bkdj7KTI2wkt"
      },
      "source": [
        "def img_text_generator(files, padded_seq, y, batch_size=None):\n",
        "    \"\"\"\n",
        "        padded_seq: vectorized padded text sequence \n",
        "        y: label of the text\n",
        "        batch_size: Number of observations to be selected at a time\n",
        "        \n",
        "        return: generator object of text data\n",
        "    \"\"\"\n",
        "    while True:\n",
        "        batch_idxs = np.random.choice(a = list(range(len(padded_seq))), size=batch_size) #Selecting the random batch indexes    \n",
        "        batch_input_txt = [] # Initializing batch input text\n",
        "        batch_input_img = [] # Initializing batch input image\n",
        "        batch_output = [] # Initializing batch output\n",
        "        \n",
        "        # Traversing through the batch indexes\n",
        "        for batch_idx in batch_idxs:\n",
        "            input_txt = padded_seq[batch_idx] # selecting padded sequences from the batch\n",
        "            output = y[batch_idx] # Selecting label  \n",
        "            input_img = get_input(files[batch_idx])\n",
        "            input_img = process_input(input_img)\n",
        "            batch_input_txt.append(input_txt) # Appending the input (text vector)\n",
        "            batch_input_img.append(input_img[0])\n",
        "            batch_output.append(output) # Appending the label\n",
        "        \n",
        "        # Return a tuple of (input,output) to feed the network\n",
        "        batch_x1 = np.array( batch_input_img )\n",
        "        batch_x2 = np.array( batch_input_txt )\n",
        "        batch_y = np.array( batch_output )\n",
        "        yield ([batch_x1, batch_x2], batch_y)"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VrTLA5XW2wdo"
      },
      "source": [
        "def text_generator(padded_seq, y, batch_size=None):\n",
        "    \"\"\"\n",
        "        padded_seq: vectorized padded text sequence \n",
        "        y: label of the text\n",
        "        batch_size: Number of observations to be selected at a time\n",
        "        \n",
        "        return: generator object of text data\n",
        "    \"\"\"\n",
        "    idxs = list(range(len(y)))\n",
        "    idx = 0\n",
        "    while True:\n",
        "        batch_idxs = idxs[idx:idx+batch_size]\n",
        "        idx = idx + batch_size\n",
        "#         batch_idxs = np.random.choice(a = list(range(len(padded_seq))), size=batch_size) #Selecting the random batch indexes    \n",
        "        batch_input = [] # Initializing batch input\n",
        "        batch_output = [] # Initializing batch output\n",
        "        \n",
        "        # Traversing through the batch indexes\n",
        "        for batch_idx in batch_idxs:\n",
        "            input = padded_seq[batch_idx] # selecting padded sequences from the batch\n",
        "            output = y[batch_idx] # Selecting label            \n",
        "            batch_input.append(input) # Appending the input (text vector)\n",
        "            batch_output.append(output) # Appending the label\n",
        "        \n",
        "        # Return a tuple of (input,output) to feed the network\n",
        "        batch_x = np.array( batch_input )\n",
        "        batch_y = np.array( batch_output )\n",
        "        if len(batch_x) < batch_size:\n",
        "            idx = 0\n",
        "        else:             \n",
        "            yield (batch_x, batch_y)"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pha4pgeeW7sV"
      },
      "source": [
        "def get_input(path):\n",
        "    # Loading image from given path\n",
        "    # and resizing it to 224*224*3 format\n",
        "    ImageFile.LOAD_TRUNCATED_IMAGES = True\n",
        "    img = image.load_img(path, target_size=(224,224))    \n",
        "    return(img)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L2eXPiB6XNlz"
      },
      "source": [
        "def get_output(path,label_file=None):\n",
        "    # Spliting the path and take out the image id    \n",
        "    filename = path.split('/')[-1]\n",
        "    # Taking list of labels\n",
        "    labels = list(label_file[label_file['image_name'] == filename]['label'].values)\n",
        "    # for duplicate selecting labels\n",
        "    if len(labels) <= 2:\n",
        "        label = labels[0]\n",
        "    elif len(labels) > 2:\n",
        "        uni_label = list(set(labels))\n",
        "        count_label = [labels.count(lab) for lab in uni_label]\n",
        "        lab_idx = count_label.index(max(count_label))\n",
        "        label = uni_label[lab_idx]\n",
        "    return label"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fHG-1CgRZMjG"
      },
      "source": [
        "def process_input(img):\n",
        "    # Converting image to array    \n",
        "    img_data = image.img_to_array(img)\n",
        "    # Adding one more dimension to array    \n",
        "    img_data = np.expand_dims(img_data, axis=0)\n",
        "    #     \n",
        "    img_data = preprocess_input(img_data)\n",
        "    return(img_data)"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P5nxoXFq2koZ"
      },
      "source": [
        "# Function to generate the data\n",
        "def image_generator(files,label_file, batch_size = None):   \n",
        "    \"\"\"\n",
        "        files: list of image paths \n",
        "        label_file: labels of the observations\n",
        "        batch_size: Number of observations to be selected at a time\n",
        "        \n",
        "        return: generator object of image data\n",
        "    \"\"\"\n",
        "    idxs = list(range(len(files)))\n",
        "    idx = 0\n",
        "    while True: \n",
        "        batch_paths = files[idx:idx+batch_size]\n",
        "#         batch_paths = np.random.choice(a = files, size = batch_size)\n",
        "        batch_input = [] # Batch input initialization\n",
        "        batch_output = [] # Batch output initialization\n",
        "          \n",
        "        # Read in each input, perform preprocessing and get labels    \n",
        "        for input_path in batch_paths:\n",
        "            input = get_input(input_path) # Load image\n",
        "            output = get_output(input_path,label_file=label_file) # Load label of the image\n",
        "            input = process_input(img=input) # Process the image\n",
        "            batch_input.append(input[0]) # Append the image\n",
        "            batch_output.append(output)  # Append the label\n",
        "            \n",
        "        # Return a tuple of (input,output) to feed the network\n",
        "        batch_x = np.array( batch_input )\n",
        "        batch_y = np.array( batch_output )\n",
        "        if len(batch_x) < batch_size:\n",
        "            idx = 0\n",
        "        else:             \n",
        "            yield (batch_x, batch_y)"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p-_zNcTV2Nwa"
      },
      "source": [
        "# Creating train, test, val, generator for meme\n",
        "img_txt_gen_train = img_text_generator(train_img_path, x_train, y_train, batch_size=32)\n",
        "img_txt_gen_test = img_text_generator(test_img_path, x_test, y_test, batch_size=1)\n",
        "img_txt_gen_val = img_text_generator(val_img_path, x_val, y_val, batch_size=1)\n",
        "\n",
        "# Creating train, test, val, generator for text\n",
        "txt_gen_train = text_generator(x_train, y_train, batch_size=32)\n",
        "txt_gen_test = text_generator(x_test, y_test, batch_size=1)\n",
        "txt_gen_val = text_generator(x_val, y_val, batch_size=1)\n",
        "\n",
        "# Creating train, test, val, generator for image\n",
        "img_gen_train = image_generator(train_img_path, training_df, batch_size=32)\n",
        "img_gen_test = image_generator(test_img_path, testing_df, batch_size=1)\n",
        "img_gen_val = image_generator(val_img_path, validation_df, batch_size=1)"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nf-C1ane2d9G",
        "outputId": "fc348aa2-a5e3-4d9b-ef1d-10249e138f32"
      },
      "source": [
        "# Creating vocabulary with glove embeddings\n",
        "vocab, w2v = read_data(os.path.join(GLOVE_DIR, \"glove.6B.50d.txt\"))"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total Words in DataSet: 400000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GnqJgOkq3U_O"
      },
      "source": [
        "#creating word index\n",
        "word_index = tokenizer.word_index\n",
        "num_tokens = len(word_index)"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NRy7nP6xBrjr"
      },
      "source": [
        "#embedding weight matrix\n",
        "embedding_matrix = np.zeros((num_tokens + 1, EMBEDDING_DIM))\n",
        "\n",
        "for word,i in word_index.items():\n",
        "  embedding_vector = w2v.get(word)\n",
        "  if embedding_vector is not None:\n",
        "    embedding_matrix[i] = embedding_vector"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LXeFyU8MCGeP"
      },
      "source": [
        "#embedding layer using embedding matrix as the weight matrix\n",
        "embedding_layer = Embedding(num_tokens + 1, EMBEDDING_DIM, weights=[embedding_matrix], trainable=False)"
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bQWm3CWUCtLE"
      },
      "source": [
        "#defining input layer\n",
        "main_input = Input(shape=(maxlen,), dtype='int32', name='main_input')"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WRSpPiJbC7dv"
      },
      "source": [
        "#embedding layer which will encode the input sequence\n",
        "embedded_sequences = embedding_layer(main_input)\n",
        "\n",
        "#LSTM will convert the sequence of vectors to single vector containing the information about the entire sequence\n",
        "lstm1 = LSTM(32, return_state=True)\n",
        "encoder_outputs,state_h,state_c = (lstm1)(embedded_sequences)\n",
        "states = [state_h, state_c]"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eN87EIOGDQdU"
      },
      "source": [
        "#second LSTM\n",
        "lstm2 = LSTM(32, return_sequences=True, return_state=True)\n",
        "#adding initial state as state of previous LSTM\n",
        "decoder_out,_,_ = lstm2(embedded_sequences, initial_state=states)\n",
        "#Dense layer with 500 neurons\n",
        "decoder_dense = (Dense(500, activation='relu'))\n",
        "\n",
        "lstm_out = (decoder_out)\n",
        "\n",
        "lstm_out = Flatten()(lstm_out)\n",
        "#output of the text model\n",
        "txt_out = Dense(1, activation='sigmoid')(lstm_out)"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EPEtK9UzEo8y"
      },
      "source": [
        "#defining text model\n",
        "txt_model = Model(inputs = [main_input], outputs=txt_out)"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lwGoviKQEz81"
      },
      "source": [
        "txt_model.compile(loss='binary_crossentropy', optimizer=adam, metrics=[\"accuracy\"])"
      ],
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 590
        },
        "id": "JPQrAUiQFBIu",
        "outputId": "423a8eec-da3e-450b-ad2f-7d972dd18f08"
      },
      "source": [
        "plot_model(txt_model, to_file='/content/drive/MyDrive/Code and Program/Stack_LSTM_txt.png', show_shapes=True, show_layer_names=True)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lgtUqJxiFMuR",
        "outputId": "68aceb00-ea5a-4c07-b2ae-3efd8f7ce88a"
      },
      "source": [
        "#Training text model\n",
        "model1 = txt_model.fit_generator(txt_gen_train, epochs=7, validation_steps=149, steps_per_epoch=2, validation_data=txt_gen_val, shuffle=False, class_weight=class_weight)"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1844: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n",
            "  warnings.warn('`Model.fit_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/7\n",
            "2/2 [==============================] - 12s 8s/step - loss: 0.8181 - accuracy: 0.5417 - val_loss: 0.7061 - val_accuracy: 0.4161\n",
            "Epoch 2/7\n",
            "2/2 [==============================] - 8s 8s/step - loss: 0.8026 - accuracy: 0.3750 - val_loss: 0.6874 - val_accuracy: 0.5705\n",
            "Epoch 3/7\n",
            "2/2 [==============================] - 9s 8s/step - loss: 0.7667 - accuracy: 0.6562 - val_loss: 0.6695 - val_accuracy: 0.6107\n",
            "Epoch 4/7\n",
            "2/2 [==============================] - 8s 8s/step - loss: 0.8691 - accuracy: 0.5417 - val_loss: 0.6714 - val_accuracy: 0.6107\n",
            "Epoch 5/7\n",
            "2/2 [==============================] - 8s 8s/step - loss: 0.8222 - accuracy: 0.5729 - val_loss: 0.6808 - val_accuracy: 0.6040\n",
            "Epoch 6/7\n",
            "2/2 [==============================] - 8s 8s/step - loss: 0.7993 - accuracy: 0.5833 - val_loss: 0.6911 - val_accuracy: 0.5638\n",
            "Epoch 7/7\n",
            "2/2 [==============================] - 8s 8s/step - loss: 0.8229 - accuracy: 0.5938 - val_loss: 0.7045 - val_accuracy: 0.4094\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bus6PXXcF_kq"
      },
      "source": [
        "txt_model.save('Stack_LSTM_txt_model.h5')"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rK5aOeGhGm2o",
        "outputId": "5e0503ed-bd49-481e-a85f-110eea874e50"
      },
      "source": [
        "#predicting the labels for the test set\n",
        "y_pred_txt = (txt_model.predict_generator(txt_gen_test, steps=149))\n",
        "y_pred_txt = np.round(list(itertools.chain(*y_pred_txt)))\n",
        "#true labels\n",
        "y_true = y_test.values\n",
        "y_true"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1905: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n",
            "  warnings.warn('`Model.predict_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0,\n",
              "       0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0,\n",
              "       0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1,\n",
              "       1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0,\n",
              "       0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0,\n",
              "       1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "cN6QSuhQHNVf",
        "outputId": "b8683c42-1ea8-4e11-f31c-709486ff6d18"
      },
      "source": [
        "#confusion matrix\n",
        "labels = [1,0]\n",
        "cm = confusion_matrix(y_true, y_pred_txt, labels)\n",
        "ax = plt.subplot()\n",
        "sns.heatmap(cm, annot=True, ax = ax);\n",
        "\n",
        "ax.set_xlabel('Predicted labels');ax.set_ylabel('True labels');\n",
        "ax.set_title('Confusion Matrix');\n",
        "ax.xaxis.set_ticklabels(['offensive','non_offensive']);\n",
        "ax.yaxis.set_ticklabels(['offensive','non_offensive']);"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P8h6AWm1Iira",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3d09d063-cd39-434b-8725-2ebfec10f4be"
      },
      "source": [
        "#creating the base model iwth imagenet weights\n",
        "pre_trained_image_model = VGG16(weights='imagenet', include_top=False)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "58892288/58889256 [==============================] - 0s 0us/step\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0S09xHLYKSFC"
      },
      "source": [
        "#create base model with imagenet weights\n",
        "base_img = Image_model(pre_trained_image_model)\n",
        "img_prediction_layer = Dense(1, activation='sigmoid')(base_img)"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tj4y4Ox6Ke_f"
      },
      "source": [
        "#defining image model\n",
        "img_model = Model(inputs = [pre_trained_image_model.input], outputs=img_prediction_layer)"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CntbBqDjKsfS"
      },
      "source": [
        "img_model.compile(loss='binary_crossentropy', optimizer=adam, metrics=[\"accuracy\"])"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "RwA-o6hFK80V",
        "outputId": "eb4fa72d-9870-4853-ea92-6165aa5fdaf1"
      },
      "source": [
        "plot_model(img_model, to_file=\"/content/drive/MyDrive/Code and Program/VGG16_img_model.png\", show_shapes=True, show_layer_names=True)"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8JzbX8vLLNVH",
        "outputId": "31840709-088f-43fc-a8d5-028dcd39ad00"
      },
      "source": [
        "#training the image model\n",
        "model2 = img_model.fit_generator(img_gen_train, epochs=7, validation_steps = 149, steps_per_epoch=2, validation_data=img_gen_val, shuffle=False, class_weight=class_weight)"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1844: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n",
            "  warnings.warn('`Model.fit_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/7\n",
            "2/2 [==============================] - 100s 85s/step - loss: 2.5529 - accuracy: 0.5729 - val_loss: 0.0621 - val_accuracy: 1.0000\n",
            "Epoch 2/7\n",
            "2/2 [==============================] - 98s 84s/step - loss: 2.3302 - accuracy: 0.6042 - val_loss: 0.0438 - val_accuracy: 1.0000\n",
            "Epoch 3/7\n",
            "2/2 [==============================] - 99s 84s/step - loss: 2.0640 - accuracy: 0.6250 - val_loss: 0.0422 - val_accuracy: 1.0000\n",
            "Epoch 4/7\n",
            "2/2 [==============================] - 98s 84s/step - loss: 1.7909 - accuracy: 0.6250 - val_loss: 0.0545 - val_accuracy: 1.0000\n",
            "Epoch 5/7\n",
            "2/2 [==============================] - 98s 84s/step - loss: 1.5332 - accuracy: 0.6667 - val_loss: 0.0871 - val_accuracy: 1.0000\n",
            "Epoch 6/7\n",
            "2/2 [==============================] - 98s 84s/step - loss: 1.3030 - accuracy: 0.6562 - val_loss: 0.1555 - val_accuracy: 1.0000\n",
            "Epoch 7/7\n",
            "2/2 [==============================] - 98s 84s/step - loss: 1.0986 - accuracy: 0.6562 - val_loss: 0.2785 - val_accuracy: 1.0000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "juTlY7a_jgEm"
      },
      "source": [
        "img_model.save('VGG16_img_model.h5')"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pQ_SKf10pmYL",
        "outputId": "0942960c-aee6-4c79-c374-36678f597445"
      },
      "source": [
        "#predicting labels using image model\n",
        "y_pred_img = (img_model.predict_generator(img_gen_test, steps = 149))\n",
        "y_pred_img = np.round(list(itertools.chain(*y_pred_img)))\n",
        "y_true = y_test.values\n",
        "y_true"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1905: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n",
            "  warnings.warn('`Model.predict_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0,\n",
              "       0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0,\n",
              "       0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1,\n",
              "       1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0,\n",
              "       0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0,\n",
              "       1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "y9PFswSpqCnZ",
        "outputId": "170e33ad-352b-46f3-b9b4-4dfc3b4bd837"
      },
      "source": [
        "#Confusion matrix for image classifier\n",
        "labels = [1,0]\n",
        "cm = confusion_matrix(y_true, y_pred_img, labels)\n",
        "ax = plt.subplot()\n",
        "sns.heatmap(cm, annot=True, ax=ax);\n",
        "\n",
        "ax.set_xlabel(\"Predicted labels\");\n",
        "ax.set_ylabel(\"True Labels\");\n",
        "ax.set_title('Confusion Matrix');\n",
        "ax.xaxis.set_ticklabels(['offensive', 'non-offensive']);\n",
        "ax.yaxis.set_ticklabels(['offensive', 'non-offensive']);"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0PWP8pzvq5Ek"
      },
      "source": [
        "txt_model.compile(loss='binary_crossentropy', optimizer=adam, metrics=[\"accuracy\"])\n",
        "img_model.compile(loss='binary_crossentropy', optimizer=adam, metrics=[\"accuracy\"])"
      ],
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TmRnAbtkrgGr"
      },
      "source": [
        "#concatenating the output of both the classifiers(text and image)\n",
        "con_layer = keras.layers.concatenate([txt_model.output, img_model.output])\n",
        "out = Dense(1, activation='sigmoid')(con_layer)"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vL2g6qVrrykK"
      },
      "source": [
        "#Common Model\n",
        "com_model = Model(inputs = [img_model.input, txt_model.input], outputs=out)"
      ],
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "REComWdur-uk"
      },
      "source": [
        "sgd = optimizers.SGD(lr=0.001, decay=1e-6, momentum=0.9, nesterov=True)\n",
        "com_model.compile(loss='binary_crossentropy', optimizer=adam, metrics=[\"accuracy\"])"
      ],
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "so2BdESBsZoE",
        "outputId": "0c09dacb-8dfd-4ad0-fc48-3a4a35168235"
      },
      "source": [
        "plot_model(com_model, to_file='/content/drive/MyDrive/Code and Program/Stack_LSTM_mul_model.png', show_shapes=True, show_layer_names=True)"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "euUQqKoQs9fI",
        "outputId": "0cc0f62c-7cce-4bec-8068-1d5b0ca409e5"
      },
      "source": [
        "#Training the combined model\n",
        "model3 = com_model.fit_generator(img_txt_gen_train, epochs=7, validation_steps = 149, steps_per_epoch=2, validation_data=img_txt_gen_val, shuffle=False, class_weight=class_weight)"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1844: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n",
            "  warnings.warn('`Model.fit_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/7\n",
            "2/2 [==============================] - 116s 98s/step - loss: 0.8071 - accuracy: 0.5104 - val_loss: 0.7364 - val_accuracy: 0.4161\n",
            "Epoch 2/7\n",
            "2/2 [==============================] - 106s 91s/step - loss: 0.8407 - accuracy: 0.3750 - val_loss: 0.7397 - val_accuracy: 0.3691\n",
            "Epoch 3/7\n",
            "2/2 [==============================] - 105s 90s/step - loss: 0.8161 - accuracy: 0.4479 - val_loss: 0.7148 - val_accuracy: 0.4362\n",
            "Epoch 4/7\n",
            "2/2 [==============================] - 105s 90s/step - loss: 0.8089 - accuracy: 0.3958 - val_loss: 0.7193 - val_accuracy: 0.4430\n",
            "Epoch 5/7\n",
            "2/2 [==============================] - 105s 90s/step - loss: 0.8032 - accuracy: 0.4062 - val_loss: 0.7288 - val_accuracy: 0.4027\n",
            "Epoch 6/7\n",
            "2/2 [==============================] - 105s 90s/step - loss: 0.8155 - accuracy: 0.3854 - val_loss: 0.7225 - val_accuracy: 0.4094\n",
            "Epoch 7/7\n",
            "2/2 [==============================] - 105s 89s/step - loss: 0.8017 - accuracy: 0.3854 - val_loss: 0.7305 - val_accuracy: 0.4228\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RlhHTCXJ4b5Q"
      },
      "source": [
        "com_model.save('Stack_LSTM_VGG_mul_model.h5')"
      ],
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vhbrDERnw6d4",
        "outputId": "00b5f732-63c8-4b9d-ec69-a10d168f8b49"
      },
      "source": [
        "y_pred_com = (com_model.predict_generator(img_txt_gen_test,steps = 149))\n",
        "y_pred_com = np.round(list(itertools.chain(*y_pred_com)))"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1905: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n",
            "  warnings.warn('`Model.predict_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "VWmCOwsKtC0Y",
        "outputId": "82e46344-46a6-4a8e-a969-638ccf51ff27"
      },
      "source": [
        "labels = [1,0]\n",
        "cm = confusion_matrix(y_true, y_pred_com, labels)\n",
        "ax= plt.subplot()\n",
        "sns.heatmap(cm, annot=True, ax = ax); #annot=True to annotate cells\n",
        "\n",
        "# labels, title and ticks\n",
        "ax.set_xlabel('Predicted labels');ax.set_ylabel('True labels'); \n",
        "ax.set_title('Confusion Matrix'); \n",
        "ax.xaxis.set_ticklabels(['offensive', 'non-offensive']); ax.yaxis.set_ticklabels(['offensive', 'non-offensive']);"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "CniJPa2vw06Q",
        "outputId": "8a1ed3e2-aa84-4bb6-9ffd-35416e882a72"
      },
      "source": [
        "# Plotting training accuaracy \n",
        "plt.plot(model3.history['accuracy'],'g')\n",
        "plt.plot(model1.history['accuracy'],'b')\n",
        "plt.plot(model2.history['accuracy'],'r')\n",
        "plt.title('Model Accuracy')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.gca().legend(('meme model acc', 'text model acc', 'image model acc'))\n",
        "plt.show()"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "GQvYeiqUo45d",
        "outputId": "5f8290fe-e1ae-4fec-ed6f-874dcdef0ed0"
      },
      "source": [
        "#plotting validation accuracy\n",
        "plt.plot(model3.history['val_accuracy'],'g')\n",
        "plt.plot(model1.history['val_accuracy'],'b')\n",
        "plt.plot(model2.history['val_accuracy'],'r')\n",
        "plt.title('Model Accuracy')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.gca().legend(('meme model acc', 'text model acc', 'image model acc'))\n",
        "plt.show()"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o4dOTJPg7SmC",
        "outputId": "e224a98c-046e-4966-c539-ee813f54dec0"
      },
      "source": [
        "#Evaluating combined model by calculating loss and accuracy\n",
        "com_model.evaluate_generator(img_txt_gen_test, steps=5)"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1877: UserWarning: `Model.evaluate_generator` is deprecated and will be removed in a future version. Please use `Model.evaluate`, which supports generators.\n",
            "  warnings.warn('`Model.evaluate_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.7952982783317566, 0.20000000298023224]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "obc1RZMw8o8g",
        "outputId": "b0a7b751-76b1-4045-f247-355c743ff1f9"
      },
      "source": [
        "#text model loss and accuracy\n",
        "txt_model.evaluate_generator(txt_gen_test, steps=5)"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1877: UserWarning: `Model.evaluate_generator` is deprecated and will be removed in a future version. Please use `Model.evaluate`, which supports generators.\n",
            "  warnings.warn('`Model.evaluate_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.6762531995773315, 0.6000000238418579]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Bu9gD4TK80dd",
        "outputId": "2bf38b0a-8a8a-4a7c-b841-d899fb4e91db"
      },
      "source": [
        "#Image model loss and accuracy\n",
        "img_model.evaluate(img_gen_test, steps=5)"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "5/5 [==============================] - 3s 462ms/step - loss: 0.5538 - accuracy: 1.0000\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.5538042187690735, 1.0]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wFYuzdzmBe6x"
      },
      "source": [
        "from sklearn.metrics import precision_recall_fscore_support"
      ],
      "execution_count": 64,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MsSvM8K0BonZ",
        "outputId": "cda8cbf5-7b16-42e1-928f-c37839145d54"
      },
      "source": [
        "precision_recall_fscore_support(y_true, y_pred_txt, beta=1.0, labels=None, pos_label=1, average=None)\n"
      ],
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0.77272727, 0.41732283]),\n",
              " array([0.18681319, 0.9137931 ]),\n",
              " array([0.30088496, 0.57297297]),\n",
              " array([91, 58]))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5uurL2z5BrfW",
        "outputId": "9ea299e5-f338-4db6-933a-cabdbe5e9f96"
      },
      "source": [
        "precision_recall_fscore_support(y_true, y_pred_img, beta=1.0, labels=None, pos_label=1, average=None)"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "  _warn_prf(average, modifier, msg_start, len(result))\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0.        , 0.38926174]),\n",
              " array([0., 1.]),\n",
              " array([0.        , 0.56038647]),\n",
              " array([91, 58]))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BJlFAI01BuTX",
        "outputId": "85cbdb56-062a-426f-dd97-cfd472d5b9da"
      },
      "source": [
        "precision_recall_fscore_support(y_true, y_pred_com, beta=1.0, labels=None, pos_label=1, average=None)"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "  _warn_prf(average, modifier, msg_start, len(result))\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0.        , 0.38926174]),\n",
              " array([0., 1.]),\n",
              " array([0.        , 0.56038647]),\n",
              " array([91, 58]))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wOY325F4Bwi5"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}