Part 1.5: Word_Embeding_Keras.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Part 03: WordEmbeding_Keras.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMgjea/1QWiiQ0Jit2cr5rW"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "-RcWdjk-_WwF"
      },
      "source": [
        "import tensorflow "
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "9ZgE_GmFB995",
        "outputId": "b837670c-eac3-4a08-d1f5-fb2f68ebf149"
      },
      "source": [
        "tensorflow.__version__"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2.3.0'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JRun0ZNsCEyc"
      },
      "source": [
        "from tensorflow.keras.preprocessing.text import one_hot"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4jJXtzRQCJe3"
      },
      "source": [
        "### sentences\r\n",
        "sent=[  'the glass of milk',\r\n",
        "     'the glass of juice',\r\n",
        "     'the cup of tea',\r\n",
        "    'I am a good boy',\r\n",
        "     'I am a good developer',\r\n",
        "     'understand the meaning of words',\r\n",
        "     'your videos are good',]"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZbcxC9mFCL85",
        "outputId": "d39dad67-5d62-4133-bcba-2d29d8dc0003"
      },
      "source": [
        "sent"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['the glass of milk',\n",
              " 'the glass of juice',\n",
              " 'the cup of tea',\n",
              " 'I am a good boy',\n",
              " 'I am a good developer',\n",
              " 'understand the meaning of words',\n",
              " 'your videos are good']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n1p8w9WtCV45"
      },
      "source": [
        "### Vocabulary size\r\n",
        "voc_size=10000"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cFci4E_PCe_Q"
      },
      "source": [
        "###One Hot Representation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QQaLlulpCZ2y",
        "outputId": "69e4a876-8292-4f4f-fed1-e3f4c03de288"
      },
      "source": [
        "onehot_repr=[one_hot(words,voc_size)for words in sent] \r\n",
        "print(onehot_repr)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[4604, 8073, 6099, 4599], [4604, 8073, 6099, 7566], [4604, 4247, 6099, 2960], [1665, 527, 6599, 2162, 7376], [1665, 527, 6599, 2162, 4498], [4965, 4604, 2908, 6099, 2686], [1496, 5150, 4418, 2162]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m6RPg9iCGEvD"
      },
      "source": [
        "#Word Embedding Represntation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BcNZkxQRCnRl"
      },
      "source": [
        "from tensorflow.keras.layers import Embedding\r\n",
        "from tensorflow.keras.preprocessing.sequence import pad_sequences\r\n",
        "from tensorflow.keras.models import Sequential"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BYQ_nXEVGZ_I"
      },
      "source": [
        "import numpy as np"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qBUu-w_UGjEf",
        "outputId": "e47ad027-ea54-48de-b42b-595c05a34546"
      },
      "source": [
        "sent_length=8\r\n",
        "embedded_docs=pad_sequences(onehot_repr,padding='pre',maxlen=sent_length)\r\n",
        "print(embedded_docs)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[   0    0    0    0 4604 8073 6099 4599]\n",
            " [   0    0    0    0 4604 8073 6099 7566]\n",
            " [   0    0    0    0 4604 4247 6099 2960]\n",
            " [   0    0    0 1665  527 6599 2162 7376]\n",
            " [   0    0    0 1665  527 6599 2162 4498]\n",
            " [   0    0    0 4965 4604 2908 6099 2686]\n",
            " [   0    0    0    0 1496 5150 4418 2162]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O1MsU4bXHyDB"
      },
      "source": [
        "dim=10"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zwmdmxU3H3zf"
      },
      "source": [
        "model=Sequential()\r\n",
        "model.add(Embedding(voc_size,10,input_length=sent_length))\r\n",
        "model.compile('adam','mse')"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dmr6CTVIIiyf",
        "outputId": "7964349d-2c43-45d2-e347-793a1d645cb4"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "embedding_1 (Embedding)      (None, 8, 10)             100000    \n",
            "=================================================================\n",
            "Total params: 100,000\n",
            "Trainable params: 100,000\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "luRNAkOII7KU",
        "outputId": "3eb216b5-9455-412b-dfa1-da0a16230e59"
      },
      "source": [
        "print(model.predict(embedded_docs))"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[[-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.0095775   0.04737971 -0.0489695  -0.01488992 -0.03347982\n",
            "    0.00616367 -0.02762285  0.01789028 -0.03286801  0.03221298]\n",
            "  [ 0.003139   -0.00097878  0.03619853 -0.02227399 -0.00534697\n",
            "   -0.01376599 -0.00829327  0.036057    0.02150379 -0.03423721]\n",
            "  [ 0.03887323 -0.00747802 -0.0429763   0.03883148 -0.03885895\n",
            "   -0.02469854  0.04596139 -0.04537367 -0.03610962  0.02099607]\n",
            "  [ 0.01247773  0.02586355 -0.00442929  0.04814162  0.00546242\n",
            "    0.01618487  0.03754207  0.03919382 -0.00736618  0.03310809]]\n",
            "\n",
            " [[-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.0095775   0.04737971 -0.0489695  -0.01488992 -0.03347982\n",
            "    0.00616367 -0.02762285  0.01789028 -0.03286801  0.03221298]\n",
            "  [ 0.003139   -0.00097878  0.03619853 -0.02227399 -0.00534697\n",
            "   -0.01376599 -0.00829327  0.036057    0.02150379 -0.03423721]\n",
            "  [ 0.03887323 -0.00747802 -0.0429763   0.03883148 -0.03885895\n",
            "   -0.02469854  0.04596139 -0.04537367 -0.03610962  0.02099607]\n",
            "  [-0.01639608 -0.04714262 -0.00697697  0.00827647 -0.04334925\n",
            "    0.00643625  0.00184067  0.01041733  0.00878062 -0.00494558]]\n",
            "\n",
            " [[-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.0095775   0.04737971 -0.0489695  -0.01488992 -0.03347982\n",
            "    0.00616367 -0.02762285  0.01789028 -0.03286801  0.03221298]\n",
            "  [ 0.0045534   0.0202573   0.01675517  0.01599002 -0.03157504\n",
            "    0.0305968   0.03410694  0.00684042  0.0097106  -0.00185434]\n",
            "  [ 0.03887323 -0.00747802 -0.0429763   0.03883148 -0.03885895\n",
            "   -0.02469854  0.04596139 -0.04537367 -0.03610962  0.02099607]\n",
            "  [-0.0483376   0.03669957  0.02294132  0.01513639  0.01535754\n",
            "    0.00205777  0.02137459 -0.0232463   0.03432128 -0.03248154]]\n",
            "\n",
            " [[-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [ 0.00266534 -0.03411236 -0.02051754  0.00904425  0.03021611\n",
            "    0.04967446  0.00060676  0.03381783 -0.03732979  0.03043855]\n",
            "  [ 0.00369409  0.02200494  0.0469391  -0.00055619 -0.02970367\n",
            "    0.01866884  0.03588284 -0.04473441 -0.0436214  -0.03209269]\n",
            "  [-0.00591307 -0.02998452  0.00978398  0.02802796 -0.01044328\n",
            "    0.02490519  0.03223938 -0.03140497 -0.02586093 -0.00290134]\n",
            "  [ 0.0281476   0.01543993 -0.00639439 -0.04956584  0.03067378\n",
            "   -0.00705458 -0.00051535 -0.01673197  0.01633049  0.01768709]\n",
            "  [-0.02064073 -0.01929143 -0.02880828 -0.03058924  0.04706744\n",
            "    0.00726181 -0.02819682 -0.00329808  0.02730477 -0.00770178]]\n",
            "\n",
            " [[-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [ 0.00266534 -0.03411236 -0.02051754  0.00904425  0.03021611\n",
            "    0.04967446  0.00060676  0.03381783 -0.03732979  0.03043855]\n",
            "  [ 0.00369409  0.02200494  0.0469391  -0.00055619 -0.02970367\n",
            "    0.01866884  0.03588284 -0.04473441 -0.0436214  -0.03209269]\n",
            "  [-0.00591307 -0.02998452  0.00978398  0.02802796 -0.01044328\n",
            "    0.02490519  0.03223938 -0.03140497 -0.02586093 -0.00290134]\n",
            "  [ 0.0281476   0.01543993 -0.00639439 -0.04956584  0.03067378\n",
            "   -0.00705458 -0.00051535 -0.01673197  0.01633049  0.01768709]\n",
            "  [-0.03755417 -0.01905615 -0.01251445  0.00777248  0.02644951\n",
            "   -0.0273616   0.03667441  0.0484359  -0.03820739  0.01509336]]\n",
            "\n",
            " [[-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [ 0.03718967 -0.0453246   0.03603914  0.0268161  -0.0342319\n",
            "   -0.02764415  0.00582004  0.00072698 -0.00532176  0.04876312]\n",
            "  [-0.0095775   0.04737971 -0.0489695  -0.01488992 -0.03347982\n",
            "    0.00616367 -0.02762285  0.01789028 -0.03286801  0.03221298]\n",
            "  [ 0.00312219  0.02082444 -0.02988657 -0.04209126 -0.04220727\n",
            "   -0.00916172  0.01381497 -0.02585714  0.03815417 -0.04725834]\n",
            "  [ 0.03887323 -0.00747802 -0.0429763   0.03883148 -0.03885895\n",
            "   -0.02469854  0.04596139 -0.04537367 -0.03610962  0.02099607]\n",
            "  [-0.00196033  0.00293012  0.03785361  0.02035106 -0.02726691\n",
            "   -0.01448668 -0.02871308 -0.04887409 -0.00569056  0.04897055]]\n",
            "\n",
            " [[-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.00569308 -0.00196759  0.04746994  0.00752538 -0.03209772\n",
            "    0.01575121  0.04804745  0.02121719 -0.01906345  0.00845637]\n",
            "  [-0.01446807 -0.02978091  0.00768944  0.00822626  0.04755614\n",
            "   -0.04625094 -0.01771615  0.02567804 -0.04097212 -0.00413238]\n",
            "  [ 0.01978124 -0.01322319  0.02456797  0.04415098  0.01182235\n",
            "    0.01630652  0.02730009 -0.01380757 -0.03194423 -0.02720731]\n",
            "  [ 0.03213834 -0.01470948 -0.03919417 -0.01447856 -0.00284035\n",
            "   -0.02161864 -0.01702936  0.03205022 -0.0168129   0.02409751]\n",
            "  [ 0.0281476   0.01543993 -0.00639439 -0.04956584  0.03067378\n",
            "   -0.00705458 -0.00051535 -0.01673197  0.01633049  0.01768709]]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B9XiRuZzJ9ME"
      },
      "source": [
        "---"
      ]
    }
  ]
}