material/deep_learning/practice/20220629_classification_voice.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "20220629_classification_voice.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "of data https://www.kaggle.com/datasets/alanchn31/free-spoken-digits"
      ],
      "metadata": {
        "id": "yNh967rsEKqw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 데이터 준비"
      ],
      "metadata": {
        "id": "PA6S3Wm8D4D4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!rm -rf mnist_audio.zip\n",
        "!wget https://github.com/dhrim/cau_2022_summer/raw/master/material/deep_learning/data/mnist_audio.zip"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Si1s0X7Z-1WA",
        "outputId": "29a16d23-b4d1-47ab-cf8d-ba821f3cce92"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-06-30 08:05:32--  https://github.com/dhrim/cau_2022_summer/raw/master/material/deep_learning/data/mnist_audio.zip\n",
            "Resolving github.com (github.com)... 140.82.121.3\n",
            "Connecting to github.com (github.com)|140.82.121.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://raw.githubusercontent.com/dhrim/cau_2022_summer/master/material/deep_learning/data/mnist_audio.zip [following]\n",
            "--2022-06-30 08:05:32--  https://raw.githubusercontent.com/dhrim/cau_2022_summer/master/material/deep_learning/data/mnist_audio.zip\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 16271789 (16M) [application/zip]\n",
            "Saving to: ‘mnist_audio.zip’\n",
            "\n",
            "mnist_audio.zip     100%[===================>]  15.52M  --.-KB/s    in 0.06s   \n",
            "\n",
            "2022-06-30 08:05:33 (271 MB/s) - ‘mnist_audio.zip’ saved [16271789/16271789]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!rm -rf mnist_audio\n",
        "!unzip mnist_audio.zip"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vKTL8DfL-1TY",
        "outputId": "69b9d922-d735-40ab-f5b8-fe664fa7ecf2"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  mnist_audio.zip\n",
            "   creating: mnist_audio/\n",
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            "  inflating: mnist_audio/9_theo_7.wav  \n",
            "  inflating: mnist_audio/9_theo_8.wav  \n",
            "  inflating: mnist_audio/9_theo_9.wav  \n",
            "  inflating: mnist_audio/9_yweweler_0.wav  \n",
            "  inflating: mnist_audio/9_yweweler_1.wav  \n",
            "  inflating: mnist_audio/9_yweweler_10.wav  \n",
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            "  inflating: mnist_audio/9_yweweler_12.wav  \n",
            "  inflating: mnist_audio/9_yweweler_13.wav  \n",
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            "  inflating: mnist_audio/9_yweweler_18.wav  \n",
            "  inflating: mnist_audio/9_yweweler_19.wav  \n",
            "  inflating: mnist_audio/9_yweweler_2.wav  \n",
            "  inflating: mnist_audio/9_yweweler_20.wav  \n",
            "  inflating: mnist_audio/9_yweweler_21.wav  \n",
            "  inflating: mnist_audio/9_yweweler_22.wav  \n",
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            "  inflating: mnist_audio/9_yweweler_24.wav  \n",
            "  inflating: mnist_audio/9_yweweler_25.wav  \n",
            "  inflating: mnist_audio/9_yweweler_26.wav  \n",
            "  inflating: mnist_audio/9_yweweler_27.wav  \n",
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            "  inflating: mnist_audio/9_yweweler_29.wav  \n",
            "  inflating: mnist_audio/9_yweweler_3.wav  \n",
            "  inflating: mnist_audio/9_yweweler_30.wav  \n",
            "  inflating: mnist_audio/9_yweweler_31.wav  \n",
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            "  inflating: mnist_audio/9_yweweler_34.wav  \n",
            "  inflating: mnist_audio/9_yweweler_35.wav  \n",
            "  inflating: mnist_audio/9_yweweler_36.wav  \n",
            "  inflating: mnist_audio/9_yweweler_37.wav  \n",
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            "  inflating: mnist_audio/9_yweweler_4.wav  \n",
            "  inflating: mnist_audio/9_yweweler_40.wav  \n",
            "  inflating: mnist_audio/9_yweweler_41.wav  \n",
            "  inflating: mnist_audio/9_yweweler_42.wav  \n",
            "  inflating: mnist_audio/9_yweweler_43.wav  \n",
            "  inflating: mnist_audio/9_yweweler_44.wav  \n",
            "  inflating: mnist_audio/9_yweweler_45.wav  \n",
            "  inflating: mnist_audio/9_yweweler_46.wav  \n",
            "  inflating: mnist_audio/9_yweweler_47.wav  \n",
            "  inflating: mnist_audio/9_yweweler_48.wav  \n",
            "  inflating: mnist_audio/9_yweweler_49.wav  \n",
            "  inflating: mnist_audio/9_yweweler_5.wav  \n",
            "  inflating: mnist_audio/9_yweweler_6.wav  \n",
            "  inflating: mnist_audio/9_yweweler_7.wav  \n",
            "  inflating: mnist_audio/9_yweweler_8.wav  \n",
            "  inflating: mnist_audio/9_yweweler_9.wav  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 파일 1개 들어보고 로딩해 보기"
      ],
      "metadata": {
        "id": "eUbbRoT7D-M_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "mG4zvhT7ES63"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import IPython\n",
        "\n",
        "IPython.display.Audio('mnist_audio/9_yweweler_9.wav')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "id": "TqROpYqRvGdP",
        "outputId": "f4bdf664-2e93-4ac7-be24-6dfbff90595c"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import librosa\n",
        "SAMPLING_RATE = 22050\n",
        "data, sampling_rate = librosa.load('mnist_audio/9_yweweler_9.wav', sr=SAMPLING_RATE)"
      ],
      "metadata": {
        "id": "V1FDJsvC2ec4"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(data))\n",
        "print(data)\n",
        "print(sampling_rate)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K_oVHKsF4_r6",
        "outputId": "c03054cd-447a-410d-89a7-3f4ae0260225"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "9667\n",
            "[-8.2852159e-05 -1.8724090e-04 -2.5001296e-04 ... -1.2657163e-04\n",
            " -7.1468705e-05  0.0000000e+00]\n",
            "22050\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(np.linspace(0, sampling_rate/len(data), len(data)), data)\n",
        "\n",
        "plt.xlabel('time', fontsize = 14)\n",
        "plt.ylabel('amplitude', fontsize = 14)\n",
        "plt.title('Length : ' + str(len(data)))\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "I9dcbi3NKIHP",
        "outputId": "0341fc86-3b7c-425d-cf77-4c6ae3f4c7c9"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "IPython.display.Audio(data, rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "id": "kVEBgTyxhlMs",
        "outputId": "4dcd22a1-cf1d-4779-90e7-76796f8705ad"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 데이터 로딩"
      ],
      "metadata": {
        "id": "633sPckREDYg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import glob\n",
        "\n",
        "file_list = glob.glob(\"mnist_audio/*.wav\")\n",
        "print(len(file_list))\n",
        "print(file_list[:3])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8HVbzOwCGAUQ",
        "outputId": "f132aff1-37c5-4ce0-fbe8-c8d33e7fc6a7"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3000\n",
            "['mnist_audio/6_nicolas_31.wav', 'mnist_audio/9_theo_49.wav', 'mnist_audio/3_jackson_8.wav']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def load_wav(file_name):\n",
        "    data, _ = librosa.load(file_name, sr=SAMPLING_RATE)\n",
        "    return data\n",
        "\n",
        "raw_x = []\n",
        "raw_y = []\n",
        "for file_name in file_list:\n",
        "    label = int(file_name.split(\"/\")[1].split(\"_\")[0])\n",
        "    print(file_name, label)\n",
        "    data = load_wav(file_name)\n",
        "    raw_x.append(data)\n",
        "    raw_y.append(label)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Aumki802EVg5",
        "outputId": "d4d9b16b-0c23-4599-ec7c-7d57df3240ec"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "mnist_audio/6_nicolas_31.wav 6\n",
            "mnist_audio/9_theo_49.wav 9\n",
            "mnist_audio/3_jackson_8.wav 3\n",
            "mnist_audio/9_theo_5.wav 9\n",
            "mnist_audio/8_theo_48.wav 8\n",
            "mnist_audio/1_jackson_26.wav 1\n",
            "mnist_audio/3_yweweler_44.wav 3\n",
            "mnist_audio/2_theo_6.wav 2\n",
            "mnist_audio/5_nicolas_21.wav 5\n",
            "mnist_audio/5_theo_25.wav 5\n",
            "mnist_audio/1_theo_12.wav 1\n",
            "mnist_audio/9_nicolas_25.wav 9\n",
            "mnist_audio/1_jackson_39.wav 1\n",
            "mnist_audio/3_lucas_15.wav 3\n",
            "mnist_audio/6_yweweler_43.wav 6\n",
            "mnist_audio/3_theo_9.wav 3\n",
            "mnist_audio/5_yweweler_48.wav 5\n",
            "mnist_audio/9_george_46.wav 9\n",
            "mnist_audio/8_lucas_19.wav 8\n",
            "mnist_audio/9_theo_1.wav 9\n",
            "mnist_audio/0_jackson_48.wav 0\n",
            "mnist_audio/9_george_26.wav 9\n",
            "mnist_audio/0_nicolas_25.wav 0\n",
            "mnist_audio/6_george_12.wav 6\n",
            "mnist_audio/0_theo_3.wav 0\n",
            "mnist_audio/4_george_32.wav 4\n",
            "mnist_audio/1_nicolas_48.wav 1\n",
            "mnist_audio/0_theo_30.wav 0\n",
            "mnist_audio/0_yweweler_2.wav 0\n",
            "mnist_audio/8_nicolas_47.wav 8\n",
            "mnist_audio/6_lucas_22.wav 6\n",
            "mnist_audio/4_george_8.wav 4\n",
            "mnist_audio/8_george_16.wav 8\n",
            "mnist_audio/5_yweweler_4.wav 5\n",
            "mnist_audio/6_george_39.wav 6\n",
            "mnist_audio/9_yweweler_26.wav 9\n",
            "mnist_audio/2_nicolas_12.wav 2\n",
            "mnist_audio/9_nicolas_42.wav 9\n",
            "mnist_audio/0_george_36.wav 0\n",
            "mnist_audio/0_lucas_6.wav 0\n",
            "mnist_audio/1_jackson_35.wav 1\n",
            "mnist_audio/1_jackson_44.wav 1\n",
            "mnist_audio/1_george_27.wav 1\n",
            "mnist_audio/0_yweweler_32.wav 0\n",
            "mnist_audio/5_nicolas_32.wav 5\n",
            "mnist_audio/2_nicolas_26.wav 2\n",
            "mnist_audio/4_nicolas_3.wav 4\n",
            "mnist_audio/4_theo_7.wav 4\n",
            "mnist_audio/0_yweweler_39.wav 0\n",
            "mnist_audio/3_yweweler_12.wav 3\n",
            "mnist_audio/6_nicolas_41.wav 6\n",
            "mnist_audio/4_nicolas_49.wav 4\n",
            "mnist_audio/2_jackson_2.wav 2\n",
            "mnist_audio/0_lucas_1.wav 0\n",
            "mnist_audio/8_lucas_11.wav 8\n",
            "mnist_audio/8_lucas_2.wav 8\n",
            "mnist_audio/5_theo_32.wav 5\n",
            "mnist_audio/7_theo_17.wav 7\n",
            "mnist_audio/4_theo_12.wav 4\n",
            "mnist_audio/2_jackson_38.wav 2\n",
            "mnist_audio/5_lucas_34.wav 5\n",
            "mnist_audio/9_lucas_37.wav 9\n",
            "mnist_audio/4_theo_4.wav 4\n",
            "mnist_audio/4_theo_24.wav 4\n",
            "mnist_audio/4_lucas_8.wav 4\n",
            "mnist_audio/9_george_15.wav 9\n",
            "mnist_audio/5_lucas_15.wav 5\n",
            "mnist_audio/4_lucas_20.wav 4\n",
            "mnist_audio/4_jackson_30.wav 4\n",
            "mnist_audio/6_jackson_4.wav 6\n",
            "mnist_audio/8_nicolas_10.wav 8\n",
            "mnist_audio/2_nicolas_16.wav 2\n",
            "mnist_audio/3_theo_5.wav 3\n",
            "mnist_audio/6_nicolas_13.wav 6\n",
            "mnist_audio/4_jackson_19.wav 4\n",
            "mnist_audio/3_theo_36.wav 3\n",
            "mnist_audio/1_george_31.wav 1\n",
            "mnist_audio/5_theo_8.wav 5\n",
            "mnist_audio/2_yweweler_22.wav 2\n",
            "mnist_audio/5_george_25.wav 5\n",
            "mnist_audio/2_lucas_35.wav 2\n",
            "mnist_audio/1_theo_8.wav 1\n",
            "mnist_audio/6_jackson_43.wav 6\n",
            "mnist_audio/6_lucas_1.wav 6\n",
            "mnist_audio/4_jackson_24.wav 4\n",
            "mnist_audio/8_yweweler_30.wav 8\n",
            "mnist_audio/9_nicolas_43.wav 9\n",
            "mnist_audio/7_george_27.wav 7\n",
            "mnist_audio/9_george_19.wav 9\n",
            "mnist_audio/5_nicolas_22.wav 5\n",
            "mnist_audio/5_theo_44.wav 5\n",
            "mnist_audio/2_theo_27.wav 2\n",
            "mnist_audio/9_nicolas_17.wav 9\n",
            "mnist_audio/7_lucas_13.wav 7\n",
            "mnist_audio/1_jackson_16.wav 1\n",
            "mnist_audio/4_george_21.wav 4\n",
            "mnist_audio/4_jackson_6.wav 4\n",
            "mnist_audio/4_theo_39.wav 4\n",
            "mnist_audio/0_george_8.wav 0\n",
            "mnist_audio/4_yweweler_5.wav 4\n",
            "mnist_audio/5_yweweler_5.wav 5\n",
            "mnist_audio/3_nicolas_44.wav 3\n",
            "mnist_audio/8_yweweler_1.wav 8\n",
            "mnist_audio/1_nicolas_41.wav 1\n",
            "mnist_audio/4_lucas_42.wav 4\n",
            "mnist_audio/3_nicolas_45.wav 3\n",
            "mnist_audio/8_lucas_8.wav 8\n",
            "mnist_audio/8_jackson_9.wav 8\n",
            "mnist_audio/4_theo_38.wav 4\n",
            "mnist_audio/6_jackson_35.wav 6\n",
            "mnist_audio/9_yweweler_24.wav 9\n",
            "mnist_audio/2_lucas_16.wav 2\n",
            "mnist_audio/8_jackson_36.wav 8\n",
            "mnist_audio/8_theo_47.wav 8\n",
            "mnist_audio/2_yweweler_3.wav 2\n",
            "mnist_audio/3_yweweler_6.wav 3\n",
            "mnist_audio/4_george_2.wav 4\n",
            "mnist_audio/7_jackson_19.wav 7\n",
            "mnist_audio/0_george_35.wav 0\n",
            "mnist_audio/5_nicolas_13.wav 5\n",
            "mnist_audio/5_nicolas_25.wav 5\n",
            "mnist_audio/0_jackson_19.wav 0\n",
            "mnist_audio/3_theo_3.wav 3\n",
            "mnist_audio/6_nicolas_20.wav 6\n",
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            "mnist_audio/0_george_40.wav 0\n",
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            "mnist_audio/1_jackson_20.wav 1\n",
            "mnist_audio/9_theo_47.wav 9\n",
            "mnist_audio/3_theo_35.wav 3\n",
            "mnist_audio/5_theo_18.wav 5\n",
            "mnist_audio/8_jackson_34.wav 8\n",
            "mnist_audio/4_theo_18.wav 4\n",
            "mnist_audio/8_yweweler_9.wav 8\n",
            "mnist_audio/4_lucas_2.wav 4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[0])\n",
        "IPython.display.Audio(raw_x[0], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "id": "LMyoGSYqiA2D",
        "outputId": "2a5b0b35-995e-4b30-cb9c-375cdb6b38a4"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "6\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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4rDmYejP7PX4cAzHIOAtEjCjKtskTiRYKTMw/TSZNkE2/jQgMkYsjyNKGjAT7w6eC7sGv/+F+C3zlO8o62zjyNjKzmfJvMkzzdbPfM/+zKLKq8mVyY/JTMrzzePVkODT6eDtbuwp6ezoCe689gb/HgR9Bs4IDg1uEuwVCRVOEFwLfQpqD8IXTh5BHkkWZAkC/ar1evT/9m35YPkV91z0ZvKU8FntUehp473h9eSN68bxjvTh82PyovKe9An2BvWu8pTyaPfG/2cGJgZq/jL0eu7t8E35lwHgBKwCMv7T+lH5LfhL9s70Efbb+s4ADgSpAp/+OPwq/hED3wbwBgkFIwbpDfAaUidfLWQsUimJKnAydD0QRShFLT+ZOGk2cjlnPvdA9D4hOZox4ylXIggbhhSID88LrwcEAdr2Tura3afTYsxlx7fDxcA5vn+7tbdtsmesdqdspfCmLaudsB62cbvhwJbGUsy30bHWoNsp4fLnbfCI+lsFGQ/BFXAYahiwGAkczyJWKrUusC1nKFAiaR77HOcb+hgUFAsPiAv6CNAE1fx68d7lWN3K2DbW6dIlzrvJ88fTyJXJDscAwR67f7ptwSTNr9dy3LHbHdrR3DDlEvDB+A797P5VAokJ/xK/Gt4d6RxaG7Yc5SHhKIsuyjBOL9MqQySxHM4VtxGaETcU+BUaE4kK6f7G9Djvve0R7UDqMuWJ4P3esODQ4tzhmdxB1f7PB9CL1crd+eSK6FvoauaB5avnK+119BL7E/8dAHj/+f67/5QBrAOBBV4H2gntDLoPTRGXEY0RKhJGE48T3RGsDjsM1Qy7EJIVFBjOFoMT+hEUFXocxiT2KT4qJSc3JHokdygeLmEyNzPSMDQtoCrmKcgp1ydJImIZcA9PB5gC0QAAAOj92vjO72vio9GFwNmzw6+LtDy9BMJevT6wuKH7mWWcdqUmrsGxVLH5sfK398LTzjnXN9tg3SrhTuhO8s39mQlaFNMbrB3PGQ0UrBLvGR4owTWgOr4zjiVxGIQStxMDFxwXWRLsCvgDy/53+ov1qe+E6crjjd7i2a7WMNZ12E7bZ9sL1yrQjMtrzS3W+eGB65vv6O6Z7NrrI+5Q85P68AIFCwwRzRPcE6YTthV4GpMfziEDIGoc0RoYHR0hJyLYHFASwwfHAjoFBgx5ER4ROQp4/8P0Le0U6kTrPe+A8zv1v/LO7JXmueOu5YLqSO4t7snqnuc86FjtOPTt+F/50/bE9DX2ivtdAjUHqge9A8D9CvlG+Ar8ggJ4CEYLewoJCKsGtAcVCnMLaAriB1YGbQdWClgMPwt0B8QDCwPJBc0JKgyWCyYJ8wYdBh4G0wUBBb4EWwb/CWEOzhFoE2YTRxIREJcMfAi4BZ0G0AvvElIXuxQ1Ch77ie365lfp1fFL+lH8m/Tk5E/TRMdgxb7MctcR3iTcnNLCxpO+HL0+wUXHzcvMzZ7OhNDc1D/bxuE15mXnU+YQ5lXqFPWHBF0TcRvHGfMQ9AfnBWoN6hohJ+wrASgUH68WZRITEu4SHBKiDowJwASjAWoAGQD0/i/7AvSl6mXiB98d4iPpaO6w7EPjEdehz8TRH9xF6JXv5O9d7DHqN+w98QP2oPgA+lv8nwCMBUIJbguIDdIQVxRuFasSQQ79DCASvhtPI6QiGBloDEUETQSjCe4N2QwNB4AALPyY+Uf2JvEo7GzqzuyT8J7xHe4g6Jfj0OK/5JfmzuZ95t3no+sK8HTy8PEc8JDvm/F59ZL5Hf1jAIMDcQWrBBcBCf3o+3H/+AWAC84M2AmFBSAD2QNLBgsIkAfsBDMBpv1I+8z6M/xT/hv//PyW+OH0JfUf+twAvAQZA5f92/jI+Gj9LwMpBh8FAQKl/zP/tP/H/2n/3v/sAYwEnAUVBHABoABrA6UIJA2KDkMNtgt7C2sLpgjOAUr5EPSc9YD81QKiAqH6X++n5xXnaeu/7qns1OUk30Ddj+AQ5QvmPuLE3DbaotwP4prmA+hW50znVulM7BTuX+6C7zj0ZPwmBK8GiwJ3+9P3m/swBbgO0hKSEH4L9gd2B+wHQgZwATz7VPbu8xXzBfLL75jsuejL4z7dotUczyDMZs0A0ZnT5tJEzzrLh8lny0nQotbf3M7htOSh5crlNOd/64zyX/qaAG8EMQf0CmgQDxafGUsawBnTGhofsSUvLLgwJjNaNNM0RTSfMjkxWzIyNyU+c0MVRGBAADwQO+E+FkW2SQZKo0VyPSEyOCSJFdkJ/QRvB4cMpwxgApruL9g9x8y/7r9RwnrCKL93uaKy9aq1oneb2ZehmQegD6jErjuzoLaBujq/J8QoyY/PN9l85i/1twGUCQ8Nuw5zEaIWCR6bJiwvYDaLOl46KjZfMEQsoStJLfot8yr/Iz8bBRPwC/4EP/0u9Vfukene5TThe9rI0pPMmMlvyR3KA8o0yQXJccryzPrOfc8Zz9fPy9O5257mOfL/+yECagR/BEoFTwnoEMIZUiBzIhAhYx9EINAjbScmKE4lECGRHk0fDSIJJBsjDR8/GWMThg7vCmEINQZpAxb/PPku89buI+0L7T/sMOmR5Mzgwd/l4Kjh598Y3AvZWNnm3OvgfOJJ4eDfMeG85RDrJO4z7m/tzu4f8zr4GPvo+hr6W/wzA1cMNROGFOEQOwzTCg8OtBPpFzcYNhW/EWYQXRFEEh0Q2gmJASD7nPma/EoABgCv+U/vpeWw4OrgY+Np5HriAt+L3Djc6Nyy3BPbotmP2mvecuMD5/fnkec86FPrC/Br9D73FfmG+37/YASpCDsLHQwYDPALJAw5DcEPrxOIF9UYBBZYEMsLTgxNEqUZXBxNF98MYwM5AL0DSAkwC0MHIgCg+r75m/y7/wsABP1o+Ib0qPLF8hT0i/UL9pn0DPGn7LfpGeqh7evxA/Sj8h7vK+yg6x3tz+5k70Lv5u8Y8tv0NPYh9c3ywPGg85D3t/qU+jv3avN28qX1Lfuf/4cANP48+1D6E/yx/nH/+Px2+MT0NvS+9tz5fvpZ9/XxmO3L7HzvGvOm9PvyiO/i7I3s3e3m7oHufu3S7YXwWfSs9tL12fLZ8DzycvY0+mP6A/eJ8wv0pflPAUkGCQZEAkz/OQBiBD8I0ghWBssD6AOCBsAI9gdBBHwAmf/qAfkE6gUWBGkBLwCvAOAAjv7M+Tz1y/MB9mX5jvoV+Lrz2fCZ8UP1Dflp+tj4+vUS9G/03PYo+hv9Kv+WACMCeASUB5QKQgwmDEQLtQsHD6MU1xm0G3QZOxVQElIS3hMMFF8Rcg2PC3YNSRG8Eq0O3gVk/Dv2JvSK8zrxaewN547jM+Lk4Fzdl9cG0lLP5M+K0XzR385qy8vJZst2zw7Uxddx2pTcc97z3zHh+OJT5o3rsfE490P7PP42Ab8ERAjCCvYL1Qy2DvQRYBUmF2kWLRSqEo4ToBbbGfIa9xj3FBUR6w5wDiYOWAx0CHYDHf+Y/Kv7/fo7+Sr2s/L+72zua+0t7J3qf+mm6fjqU+x07B3rYOnM6C/qG+1r8Ebzh/Vh98/4kfnE+U76avyTANIFNgpFDBkMOgtTC/YMdA+oEeMSDBMwEksQow04C2AKhwsoDW4MZQcX/3H3k/R699n8af/k+4Tz4OpA5nTm1OgK6vPoEOdi5hDnN+cT5Tnhh96X3xPkj+hW6dHlZOHe4InmKfCq+PD7wfmB9VvzV/WD+loAygQoB+YH4QcECDoJGAwxEN0TFhUcE2EPqQzZDFEPaxHOEIQN4AlPCBoJQgqJCaIGbgMTAtUC1gP0Auj/jfwe+yT8Df7C/n79NvtY+WD4sve49s713PUZ92z4Xvi79g31O/V497j5avkM9vzxjfAR85b3rvqX+sX4U/jY+r/+wgAn/4T7XPnK+nf+2gCL/377E/jL9+f5IPvV+Jjzuu417fDu0/Cl7/Pqb+V/4kvj8uVt503myONV4lXj9OUy6N3olOjt6LbqJO2s7sfuv+6z8JP16/usAHYBfv6O+hb5yvudAbkHfAsHDFUKLQj3BjoHwAjsCuQMrw2gDOQJsgauBLgELgZnBxoHjwVeBOUE1wZLCGoHQQTxAOz/xAGfBNUFUgSLARgAVwFGBKIGDwcvBqEFEAZxBjoFSQJe/3n+sv/TAGX/Q/sr93P24/nB/gQByv7c+fD1U/Uq97L4JvhI9kL1Mvb795f4V/eq9Yz1Ove0+K33+/MH8JnuMvCW8gzzFvHd7uXuT/GY8yTzEfBq7UnurPIg98f37/PA7mfsXO5T8rX0I/SU8gnzQvbV+ZH6y/c59GXzNPbr+cn6u/eU83ny+PVr+0z+RPw192jzqfP19sb5gfnH9oL05/Rc90X5vPhr9sH0bfWy9zL5Y/gW9qn0m/UK+In5evix9cbzzPSW+AT94v+NAPz/fv+a/wUAVwB7AHAA4P9R/v77NPqF+kH9wACFAl4BrP5Q/SD/GgMzBgwGHwNPAD0A3gKZBckFNwNNANT/bwIuBlYIqQcUBW0CygAFAJr/gf///70AkACE/kD7Ffkp+kT+gwKMA30A1/th+dL6Uv4vAEL+vfny9Tf1+Pah+Ez4d/Y79e/1yPfC+M336/Ue9Un2SPgQ+b/3WfWW8xDzz/Kj8cLvxe7l71Pyq/M/8hbvTe047+XznPcY95zy3O247LTvl/OE9K7xI+7k7RDyu/eZ+u/4GfU981r1bPlX+9L4mvP47+7wmvUW+vL6GPiZ9LXz/vUO+fP56/cA9Qb09PX8+DP6RPi99Nry1PT4+ST/MAFi/9X7tvmx+rj9BQCE/5X8yvnC+e78HwE7A7QBx/1k+s755vuS/tD/e/85/58AcQOoBWYF4QJwAHcAEQPQBekF9wKe/0j/8wL+B0EKuQdxAs3+pv++A9sGlgVuAEb71fla/JT//v8o/QL63fkS/YoArADa/CL4avbG+HL8dP1Z+o71CPOQ9DP4Qvrj+LL1+vNm9WT42flM+F71HPTa9dP48Pnz9870wPMP9pz50PoY+HzzxfDz8Vf1Ovdd9Qvxyu0I7vHwc/M+89PwxO4M7zTx+fKl8qjwBe9B7xPx+/Lz82L0W/Uj96z4qfgO9071E/Wt9uD4RPqz+j77ufx+/vD+Xf1D+1z7Gf/lBCUJRAkYBjEDmAPqBpYJHwhwAiH8XflA+/3+jgBs/sj6U/mX+3b/JQG9/gP6z/aA99z6Q/0L/OH3E/SD8yX2Ofnr+dL3DPUl9M/1jvhe+pX6Ifoj+on6JPon+Gb15fMH9Rn40/pr+0z6u/mi+4j/wwLDAmr/S/uF+Rr7Lf7R/6f++vtq+mr78/2O/6j+Dfwr+uT64v32ABIC/ABP/77+Y/+b/5v9VPnf9OzyivQb+If6tflR9kzzdvMb96L7m/2I+xr3yfPw8+H2lvl7+cL2RvT19Bv58v0MAFj+FvvH+ej7g//xAEn+TfkK9kj3CfxgAO4AzP1D+q35YvyL/wAAX/1k+i/6B/3g/x3/I/pE9AjyKfXu+nX+3fyu90/zFfN59uP5IvpK91n0LvTQ9oX5mvkD9170WvQK98v5zPnb9rHzgPP29oT7kP2P+zv38vPV80D21fjP+XX5afnQ+jv9Qf8HAAEALgDNAPMAl//v/Kv6ifqk/Bj/nf+X/cX6zfnp+8T/jgJPAmH/5/vr+c35Yvpl+rX5Ovm6+c/6I/uv+dj2VPTk8/f1TPnS+wr88PnW9oP0K/Td9ZP40fp4+3r68Phq+Nv5wPxb/+X//f0e+6z5HPvB/iEC0AJFAFf80flP+gr9hP+h/1T9pvr7+RX8f//UAb4B/P+H/sX+SgBuAfsAbf9z/jn/EAHzAWIA9Pzr+Sz5Yfo++7L5EPYJ81TzHvei+2z9Q/sf91X0rfQT9+T4f/ig9l/19/Wa92z4f/fc9YT1fffQ+nP9Gv42/Ur8Xvws/bD9W/2e/Fj81PyA/Zn9Af1c/GH8F/3R/dP97Pxz+9D5N/jN9u31/fXo9ub3BfgS9/D1zfXt9jz4Ufjs9mL1ZPUu9w357viN9hH0PfS19wv8pv38+hj26PLP84r3avrA+U/2oPPZ9P75/v9EA3MCAf+h+y/61Pqz/OH+twCKAasAEv72+mH5s/pN/sYBswKKAAL9n/q0+pP8cf7w/vX9Qvyd+mD5tvjd+Oj5R/vT+6z6JfjE9Q/1Nvbg9234c/cU9sb1z/b+9/L3pPae9Y32jPnk/Ij+5v1V/LP7mvzy/TX+E/3H+8n7Mf2M/kv+dvzU+lD7Gv5PAaACXQEK/+z98f7qANMBzQD+/lj+lv9YAVEBfv5L+oP36PeY+sf8IfzO+EP1EfS19Un4Uvn897/12fQj9kX4CvmR91j1BvX699P8VwAFADb87/eI9g/5hf2QACgAGf0z+vH5dfyG/24AMv5U+pz30fdJ+nf8APy++Oj0U/ML9Wr4bPo7+dH1N/Pz89H3+ftB/c36rvYR9JP0GvcV+dn47PZC9Un1wvZa+DT5uPnf+tb8jf64/kT9m/tg+8z8bv6U/g79avtl+xn9zP6m/qz82/o2+5r9qP8I//P7WflM+uX+qgNRBIP/NfhV86vzoPfb+iv6Qvbe8kjzbPcA/Hn9APvb9kL0p/Tr9r74uPhA98T1XvUq9qH3Pfmk+nT7Pvv5+XX4BPhz+Sn8dP7l/o797PuK+578+P06/jX9Bfzl++v8Af4E/vP86fv8+yH9Nf4b/tP8gvtw+/38Yf9MAbcBQgAw/VT59vVk9CP1V/cY+dn4yfbP9OH0HPdz+X353fbh85bz6vaJ+7X9jfvG9k/z/fNK+Ab9Kf8t/v778vra+9j9qf/FAFQBWwFyAG7+IvwR+wX8BP7d/hX9X/kf9kv1svZK+EH4t/Z09ej1nvez+OD38PX99Df2fvhf+Z33ufS/81f25/q6/UP8h/dR8+nyNPbs+ab63vdJ9EDzuvWZ+cv7MfuO+bf50fwZAWYD6gHP/Tv6tvkh/Ab/y//r/UH7S/rt+6T+4v9Z/kP7dfn0+hb/1wI/A97/Q/v0+Hv6Jf6CAHX/CvyE+Vf63P3MAD0AS/wR+OT2Rvl3/AX99/mm9Ybz9vQb+MX5fvjL9Xr0zvVL+FH51/d29bn0b/bE+CD5/va79Gj1pvmv/qwAWf5Q+tL40PsRASoEdgJ2/WH5Ufmj/NT/8P8x/X36c/rv/Fr/U//1/Kb6r/oM/Xz/ov8o/eP5GfiO+Cb6Lvvj+tz5LflS+fP5ePqe+nb68PnD+Nz28/Rb9PT1KvkB/Gv86vkd9qHzGvTz9tL5V/rl9wz0ZPG18bb0Ufgf+h75Y/ZK9J/0J/e1+eP5K/ev87ryGPZD/DUBagG8/Lb27vNk9vf7NQAaAHz8Lvmf+dj9gwLVA80A+/sv+Tz6m/0AAFn/hPxN+sX6ZP2f/0//sPwr+i/6Cv2lAGUCYwEd///9KP9jAT8CUgCb/Mn5+fnU/Mf/KACL/S76K/nL+1MAWQOJApX+l/p/+az7xf7o/zD+aftF+tb7j/7C/zL+Ufvz+Zz78P6/AOz+c/rE9t72s/oy/+YA5f5p+7n5O/tX/hAA0P7H+8j5vfoC/hsB9gGfAO7+p/7j/ysBFwG6/5D+Af/XADkCIQEn/f73V/T886D2M/pS/MP7A/nK9evzWPS89rr5tfuh+5b5t/aS9En09fWs+AT7yfuQ+un3J/XP88j0tvf7+oz8TPvy97j0zPOl9ZL4Bfqu+KH1jPOA9Cf47PsD/ab6q/b980301PYu+WL5b/cc9Wf08/Wx+OX6fvuz+o/5BflR+RD6tfrk+nn6afnR9x72EfVa9QL3Pfnh+lf7L/u3+8L9qgCFApoBB/4G+nz4sfot/7kC3QLD//f7Q/pr+8j9/v4Y/jn8Ufsu/M79f/6Y/Rr8lvuR/Pz9Wf5D/d/7qfvh/Eb+V/7x/IH7lvs4/cb+iv6P/MD6Ifuz/SUAxP/a+4b2DPNB80H2e/nq+n36l/lx+QT6bfon+qP5svlp+sf6pvkM94D06/Pw9UP5pPu5+xX6mvi5+DP6bPsL+1f5G/gH+RP8Tv9lAJ3+bfs4+Sz5NPoQ+p73P/Tg8k31Ovro/TT9cPhx837yp/a9/Ov/yv1a+CX0N/SQ91H6f/nO9e7yAvSZ+AL9mP38+Uz1PfPs9Cz40fma+Ab2mPRw9Yn3IfmX+df5Evs2/eb+3f4//WX7bvoa+jj5O/cz9RD1zfdU/EMA4wFiAUAAnv85/x/+M/y9+jn7mP3P/4f/XvyN+A732/jk+9b8NfrN9SrzUvTg90z6PvnV9bzzxvU6+zwAIAGP/b/4mfZP+Iz72vzt+tP38fa++Ur+9QC//xP8fvli+s79bQCy/z38UfnO+Yz9hgGuAqwAEf66/Q4AmgJ7Ajb/QPu7+Yj7g/6o//f9WPuc+pb8Iv8l/6H77/bZ9EX3dfxrADsAWfwI+J728/gZ/SoAeABQ/jX7e/iE9uj0DfOr8Abu++vL64nuTvS/+3sCVQZ4BqYDa/8M+zP3XPRC85L0FvhL/CT/ev/h/Qr8L/sM+2P6gPgp9v70z/Wv97H4y/fv9Uz1T/c5+6b+fv+T/ZP6f/g0+CT5S/ow+xD8Sf3K/iIA8gAjAcAAvP8Q/iX85vou+wX9ZP/wAAoBMwB9/4X/BgBTACIAz//R/ycAVgAKAJD/if8jAMMAmQCf/9D+O//CAOsBJgFp/nr7dfri+yv+Gf/k/dz7D/s8/Cn+6f7K/d37p/pf+qT5BvfI8gjvAO4g8NTzIvdl+WL7uP19/8P+o/rI9KLwv/CZ9PT4kfrE+Lf1QvRt9dj3RPme+J32tPSh8x7zuvLK8jL0U/dB+zj+8f6Y/Xv7z/nJ+Nj3qvbY9YL2N/k6/dMAgwIAAj4Alv63/Vn9qvwz+1H5A/gm+Mr5FPzW/V/+2/34/C78WPsX+pf40ffQ+Ij7b/6F/x3+rPum+jD8yv54/5L8tPe39Fz2mvs7AIgAr/zD+BP5Gf7JAwgFMgCl+OPz7fQC+o7+W/8J/dX6L/uB/S7/dP4u/ND6yvsP/jX/Af6r+6P6FPyp/sf/Dv6i+gz45feK+Q77TfsD+9v7c/5zAZoCxwAN/c/5wvip+d76+Pr4+f74DfkS+hX7JfsT+lv4nfZK9c30uPVk+Ez8zP/4ABD/TPs4+Mz33/k2/Fn8ovnZ9dXzQfVL+VL9+P7l/dv7Hvt0/Gj+bP4B+zz1YPCz7w70Cft8AF4B5v08+f/2cvin+0P9Y/s39/fzLPSs9+X7Kf7K/Uz8q/uL/Ob9Vv58/Sb8Kftn+hL57/YX9UD1Evg1/CX/Lf+//On5g/jN+Lb5Sfqn+qn7pP3Q//oAxQABALj/6f90/1/9Mvre9xn4v/ra/XT/Wf8R/wQAxQE4ArP/2vpv9vD0afZ6+Kv4z/Yp9Sr2AfpA/v3/U/4D+6P4Q/i/+D34R/Zm9LX02fdg/Pz/YAHtALr/H/56+1T3vvI78OvxevfU/SUBwv+F+2/4gvlT/k0DegSUAAb6FvW19Hz4Q/21/7f+0fuA+QH5hvlC+T33RPQx8lDyYvQO9zb51/q6/EP/pAFDAgoAfPud9sTzL/Rr9777LP9lADj/hPzJ+W/4/vit+tL7Afs6+Cf1DvQo9qn6AAA=\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[1])\n",
        "IPython.display.Audio(raw_x[1], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "id": "bjXXExOuiHcr",
        "outputId": "bfcd0e5d-1af8-4826-d64c-1741eb9420a4"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "9\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[2])\n",
        "IPython.display.Audio(raw_x[2], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "id": "WZspsg4piHZM",
        "outputId": "cd0df048-fbb9-4a1c-f3b5-59da1ae81af0"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "gUMz9NiniHVE"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# padding"
      ],
      "metadata": {
        "id": "M1e1eHmSNfY9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lens = []\n",
        "for i in range(len(raw_x)):\n",
        "    lens.append(len(raw_x[i]))\n",
        "\n",
        "plt.hist(lens, bins=100)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "FsjDBDIOEVd4",
        "outputId": "d661dfc2-22e8-4b98-b181-9b73e684c26e"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow.keras.preprocessing import sequence\n",
        "\n",
        "padded_raw_x = sequence.pad_sequences(raw_x, maxlen=22000, padding='post', dtype=float)"
      ],
      "metadata": {
        "id": "aghztZe9-1N5"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "jZN23FcoiUub"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[0])\n",
        "IPython.display.Audio(raw_x[0], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "696fb594-8bb7-4e58-bb28-70af3bd68d6f",
        "id": "7mTCyMzWiVAZ"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "6\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[1])\n",
        "IPython.display.Audio(raw_x[1], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "7147b44a-3ee6-4752-9bc9-6f31a1c811b8",
        "id": "R6-jXew3iVAZ"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "9\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[2])\n",
        "IPython.display.Audio(raw_x[2], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "c1f83c88-c083-421a-c695-bfbc6ebd6d89",
        "id": "LmV1t8nWiVAZ"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "raw_x = np.array(padded_raw_x)\n",
        "raw_y = np.array(raw_y)\n",
        "print(raw_x.shape)\n",
        "print(raw_y.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1b-zDbF--1LQ",
        "outputId": "413d497a-34d7-4ba0-f436-e800dfca3f40"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(3000, 22000)\n",
            "(3000,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "3qx8sP10ia9h"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[0])\n",
        "IPython.display.Audio(raw_x[0], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "cc51d583-877a-4a02-b0df-7e97ef5d341a",
        "id": "kvxddiJmibQf"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "6\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[1])\n",
        "IPython.display.Audio(raw_x[1], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "eac1e8d4-e576-48e2-d512-07e0e8942e85",
        "id": "o02lV35TibQg"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "9\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(raw_y[2])\n",
        "IPython.display.Audio(raw_x[2], rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "bbed6564-523b-488b-de4e-dad66e62ac15",
        "id": "74-W5hqAibQg"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Normalization"
      ],
      "metadata": {
        "id": "fMc7mKiONdAs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "max = np.max(raw_x)\n",
        "min = np.min(raw_x)\n",
        "print(min, max)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yb7uzqDONoSF",
        "outputId": "8eecc49c-5a32-4127-c946-7706c065c588"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "-1.0124074220657349 1.0405950546264648\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# raw_x = (raw_x - min) / (max - min)"
      ],
      "metadata": {
        "id": "xjE3MuKwNcGt"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2차원으로 reshape"
      ],
      "metadata": {
        "id": "T-iyrW8_N869"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "raw_x = raw_x.reshape((len(raw_x),-1,1))"
      ],
      "metadata": {
        "id": "EXF8sZPYN_RL"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 데이터 분리"
      ],
      "metadata": {
        "id": "EjXer_ucN67c"
      }
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "7xHpzZWbRlXW"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "train_x, test_x, train_y, test_y = train_test_split(raw_x, raw_y, test_size=0.2, shuffle=True)"
      ],
      "metadata": {
        "id": "Z54gJGmi-1Ig"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(train_y[0])\n",
        "IPython.display.Audio(train_x[0].squeeze(), rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "57e14087-c7c4-4481-a98e-31f8734c67a9",
        "id": "ar3Q1ezWinMR"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "7\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(train_y[1])\n",
        "IPython.display.Audio(train_x[1].squeeze(), rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "5a278dab-4c8b-4f8d-f83c-08996476c791",
        "id": "RFKC_o3IinMS"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(train_y[2])\n",
        "IPython.display.Audio(train_x[2].squeeze(), rate=SAMPLING_RATE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "3119b4d2-d3d1-406d-85e1-aff1757379fd",
        "id": "loZi4itvinMS"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# copy from https://gist.github.com/stared/dfb4dfaf6d9a8501cd1cc8b8cb806d2e\n",
        "\n",
        "from IPython.display import clear_output\n",
        "from tensorflow.keras.callbacks import Callback\n",
        "\n",
        "class PlotLosses(Callback):\n",
        "\n",
        "  def on_train_begin(self, logs={}):\n",
        "    self.epochs = []\n",
        "    self.losses = []\n",
        "    self.val_losses = []\n",
        "    self.logs = []\n",
        "    self.fig = plt.figure()\n",
        "\n",
        "\n",
        "  def on_epoch_end(self, epoch, logs={}):\n",
        "\n",
        "    self.epochs.append(epoch)\n",
        "    self.losses.append(logs.get('loss'))\n",
        "    self.val_losses.append(logs.get('val_loss'))\n",
        "\n",
        "    clear_output(wait=True)\n",
        "    plt.plot(self.epochs, self.losses, label=\"loss\")\n",
        "    plt.plot(self.epochs, self.val_losses, label=\"val_loss\")\n",
        "    plt.legend()\n",
        "    plt.show();\n",
        "    print(\"loss = \", self.losses[-1], \", val_loss = \", self.val_losses[-1])"
      ],
      "metadata": {
        "id": "xULPFYqYA4Pv"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow import keras\n",
        "from tensorflow.keras.layers import Dense, RepeatVector, Flatten, Input, Activation\n",
        "from tensorflow.keras.layers import Bidirectional, LSTM, GRU, Conv1D, MaxPooling1D, AveragePooling1D, Add, MaxPool1D\n",
        "from tensorflow.keras.layers import Dropout, GaussianNoise, BatchNormalization\n",
        "from tensorflow.keras.regularizers import l1, l2, L1L2\n",
        "from tensorflow.keras.optimizers import Adam\n",
        "\n",
        "input_shape = train_x.shape[1:]\n",
        "# input_shape = (5,1)\n",
        "\n",
        "model = keras.Sequential()\n",
        "model.add(Input(input_shape))\n",
        "model.add(GaussianNoise(0.01))\n",
        "\n",
        "for i in range(13):\n",
        "    model.add(Conv1D(64, 3, padding=\"same\", activation=\"relu\", kernel_regularizer=l1()))\n",
        "    model.add(BatchNormalization())\n",
        "    model.add(Dropout(0.2))\n",
        "    model.add(MaxPooling1D())\n",
        "\n",
        "model.add(Flatten())\n",
        "model.add(Dense(64, activation=\"relu\", kernel_regularizer=l1()))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Dropout(0.2))\n",
        "model.add(Dense(10, activation=\"softmax\"))\n",
        "\n",
        "model.compile(loss=\"sparse_categorical_crossentropy\", optimizer=Adam(learning_rate=0.0001), metrics=[\"acc\"])\n",
        "model.summary()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q212AjwQ-1Fy",
        "outputId": "ba93951b-64c2-4ba5-864e-f9690923a9d7"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_2\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " gaussian_noise_2 (GaussianN  (None, 22000, 1)         0         \n",
            " oise)                                                           \n",
            "                                                                 \n",
            " conv1d_26 (Conv1D)          (None, 22000, 64)         256       \n",
            "                                                                 \n",
            " batch_normalization_28 (Bat  (None, 22000, 64)        256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_28 (Dropout)        (None, 22000, 64)         0         \n",
            "                                                                 \n",
            " max_pooling1d_26 (MaxPoolin  (None, 11000, 64)        0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_27 (Conv1D)          (None, 11000, 64)         12352     \n",
            "                                                                 \n",
            " batch_normalization_29 (Bat  (None, 11000, 64)        256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_29 (Dropout)        (None, 11000, 64)         0         \n",
            "                                                                 \n",
            " max_pooling1d_27 (MaxPoolin  (None, 5500, 64)         0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_28 (Conv1D)          (None, 5500, 64)          12352     \n",
            "                                                                 \n",
            " batch_normalization_30 (Bat  (None, 5500, 64)         256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_30 (Dropout)        (None, 5500, 64)          0         \n",
            "                                                                 \n",
            " max_pooling1d_28 (MaxPoolin  (None, 2750, 64)         0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_29 (Conv1D)          (None, 2750, 64)          12352     \n",
            "                                                                 \n",
            " batch_normalization_31 (Bat  (None, 2750, 64)         256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_31 (Dropout)        (None, 2750, 64)          0         \n",
            "                                                                 \n",
            " max_pooling1d_29 (MaxPoolin  (None, 1375, 64)         0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_30 (Conv1D)          (None, 1375, 64)          12352     \n",
            "                                                                 \n",
            " batch_normalization_32 (Bat  (None, 1375, 64)         256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_32 (Dropout)        (None, 1375, 64)          0         \n",
            "                                                                 \n",
            " max_pooling1d_30 (MaxPoolin  (None, 687, 64)          0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_31 (Conv1D)          (None, 687, 64)           12352     \n",
            "                                                                 \n",
            " batch_normalization_33 (Bat  (None, 687, 64)          256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_33 (Dropout)        (None, 687, 64)           0         \n",
            "                                                                 \n",
            " max_pooling1d_31 (MaxPoolin  (None, 343, 64)          0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_32 (Conv1D)          (None, 343, 64)           12352     \n",
            "                                                                 \n",
            " batch_normalization_34 (Bat  (None, 343, 64)          256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_34 (Dropout)        (None, 343, 64)           0         \n",
            "                                                                 \n",
            " max_pooling1d_32 (MaxPoolin  (None, 171, 64)          0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_33 (Conv1D)          (None, 171, 64)           12352     \n",
            "                                                                 \n",
            " batch_normalization_35 (Bat  (None, 171, 64)          256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_35 (Dropout)        (None, 171, 64)           0         \n",
            "                                                                 \n",
            " max_pooling1d_33 (MaxPoolin  (None, 85, 64)           0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_34 (Conv1D)          (None, 85, 64)            12352     \n",
            "                                                                 \n",
            " batch_normalization_36 (Bat  (None, 85, 64)           256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_36 (Dropout)        (None, 85, 64)            0         \n",
            "                                                                 \n",
            " max_pooling1d_34 (MaxPoolin  (None, 42, 64)           0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_35 (Conv1D)          (None, 42, 64)            12352     \n",
            "                                                                 \n",
            " batch_normalization_37 (Bat  (None, 42, 64)           256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_37 (Dropout)        (None, 42, 64)            0         \n",
            "                                                                 \n",
            " max_pooling1d_35 (MaxPoolin  (None, 21, 64)           0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_36 (Conv1D)          (None, 21, 64)            12352     \n",
            "                                                                 \n",
            " batch_normalization_38 (Bat  (None, 21, 64)           256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_38 (Dropout)        (None, 21, 64)            0         \n",
            "                                                                 \n",
            " max_pooling1d_36 (MaxPoolin  (None, 10, 64)           0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_37 (Conv1D)          (None, 10, 64)            12352     \n",
            "                                                                 \n",
            " batch_normalization_39 (Bat  (None, 10, 64)           256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_39 (Dropout)        (None, 10, 64)            0         \n",
            "                                                                 \n",
            " max_pooling1d_37 (MaxPoolin  (None, 5, 64)            0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " conv1d_38 (Conv1D)          (None, 5, 64)             12352     \n",
            "                                                                 \n",
            " batch_normalization_40 (Bat  (None, 5, 64)            256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_40 (Dropout)        (None, 5, 64)             0         \n",
            "                                                                 \n",
            " max_pooling1d_38 (MaxPoolin  (None, 2, 64)            0         \n",
            " g1D)                                                            \n",
            "                                                                 \n",
            " flatten_2 (Flatten)         (None, 128)               0         \n",
            "                                                                 \n",
            " dense_4 (Dense)             (None, 64)                8256      \n",
            "                                                                 \n",
            " batch_normalization_41 (Bat  (None, 64)               256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_41 (Dropout)        (None, 64)                0         \n",
            "                                                                 \n",
            " dense_5 (Dense)             (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 160,970\n",
            "Trainable params: 159,178\n",
            "Non-trainable params: 1,792\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_losses = PlotLosses()\n",
        "history = model.fit(train_x, train_y, epochs=100, verbose=1, validation_split=0.1, batch_size=16,\n",
        "                    callbacks=[plot_losses])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        },
        "id": "JfLBEaJ9_UZE",
        "outputId": "a2bd313b-4ef5-44d5-bbe8-729589380675"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loss =  3.6109893321990967 , val_loss =  3.9369661808013916\n",
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r135/135 [==============================] - 4s 31ms/step - loss: 3.6110 - acc: 0.7727 - val_loss: 3.9370 - val_acc: 0.6000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "history = model.fit(train_x, train_y, epochs=100, verbose=1, validation_split=0.1, batch_size=16,\n",
        "                    callbacks=[plot_losses])"
      ],
      "metadata": {
        "id": "6wEi3TWQr5uQ",
        "outputId": "14df846d-30c6-4068-b0e0-8df91de60756",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        }
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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aLwGABZudZMoYBbqcTYiCZem/PLYzMDUajcZVjktB7xUXTveuYSzc5MR2MSwXZxOioCwX2QANtZ4foEaj0XQAx6WgCyE4rV8CS7YXUV3X0HSHLukw9EoYeKHzg+iuRRqNxsc4LgUdYELfeKrrTCzbcbjpk/6BcMF/lYfuDN1XVKPR+BjHraCP6RVLSKAfC5zZLi2huxZpNBof47gV9JBAf07uHceCzYXI1kxs6q5FGo3GxzhuBR1UtsueI5VsPlju/osNQdddizQajY9wXAv65KwkwoP8efmnLe6/WE+KajQaH+O4FvS4iGBumdCb+XkHWe5ocrQ5GgVde+gajcY3OK4FHeD6U3qRFBXCc99vxGRyw0vXEbpGo/ExjntBDw3y5/5JfVlbUMo36/a5/kLrSVEpYfbV8M1deuWoRqM5bjnuBR3gwmEpDEyO4u/zNjteaOQIa8sl70vYOBdWvQtrPvDeQDUajcaL+ISg+/kJHj2nP3tLqnjqmzzX0hiNCL3yCPz0V0jMgp7j4YcHVacjjUajOc7wCUEHOKl3HLdO6M3HK/J5/49dLb/AEPSVb0HpHpj8PFz4hnp8zvVQV+3V8Wo0Go2nabF87vHEfWf2Zeuhozz97QZ6J0QwNqOZNndCKNulsgj6nQs9x6nHL3gdProMZpyimktXl6nnLnqjfT6ERqPRtBKfidBBWS8vTx1KRkIkt81azZ7DLWSwBIaCXyBMfNryWOYkmPwCRCVDXCZExMP6z3V6o0ajOebxKUEH1dHorWtHUl1v4p0lO5vfudepcOojENvb9vExf4Fr58LUD2D8Q2Cqg305tvvUHIVDXuu0p9FoNG7jc4IOkNY1jIn9E/k6Zy+19SbnO17yNoy9p/mDpY5S2/zlto8vfB7+dxo01LdtsBqNRuMhfFLQAS4ekUJxZV3zvUddISIeuvaCgpW2j2+Zr3LYy/e37fgajUbjIXxW0MdlxBMXEcznqwrafrC0E1SEbqRDFu+Gw1vV7VIPHF+j0Wg8gM8KeoC/HxcMTWbB5kMcqWhjm7m00VBRCMVmT377L5bntKBrNJpjBJ8VdICLhqdS1yD5Zq0bJQEckTpabfPNtsu2XyAiUd0u3dO2Y/siK/4HuXM6ehQaTaejRUEXQoQIIVYIIdYKIfKEEE852CdYCDFbCLFNCLFcCJHujcG6y4DkKPp3i+Lz1W2MohP6Q1Cksl0a6mDHb9D3LAjtqiN0R6x8G3JmdfQoNJpOhysReg1wmpRyCDAUmCyEGGO3z/VAsZSyD/Ay8IJnh9l6Lh6ewrqCUra2pgmGgZ8/pI6E/BVqcrS2HHqfDtGpWtAdUVeh0jo1Gk270qKgS4Xx1xlo/mdfLGUK8L759hzgdCGE8Ngo28CUoSkE+gveWbKrbQdKOwEO5cGGr0H4Q6/xEJ2mBd0RtRXqn0ajaVdc8tCFEP5CiBzgEPCTlNIuKZsUIB9ASlkPlAKxnhxoa4mPDOaK0d35NDufHYVtiBrTRoE0war31CRpSDTEaEF3SG2luorRaDTtikuCLqVskFIOBVKB0UKIrNa8mRDiJiFEthAiu7CwsDWHaBW3n5ZBcIAfL/7YhiqKKSMBAfXVym4BZbnUlEFVSdP966rV5ODMC2D/2ta/7/GGqQHqq7TlotF0AG5luUgpS4AFwGS7p/YCaQBCiAAgGmjSE05K+aaUcqSUcmR8fDOFszxMfGQwN47txfe5B8jJdyC+rhAaoyZHAfpYCTrYRummBlj2OrwyBL6/D/Ysg3fPhq0/t/4DHE8YHaC05aLRtDuuZLnECyFizLdDgYnAJrvd5gLXmm9fAvwqXSpK3n7cOK4XseFB/O2Hja7VS3dErwkQlQLdhqr70Wlqay3ouZ/BvIdUfZhr5sL0NdC1p6rguHpmWz7C8UGtWdAbalRGkEajaTdcidC7AQuEEOuAlSgP/VshxNNCiPPN+7wNxAohtgH3AA95Z7itJyI4gOmnZ7Bsx5HWlwM4/a/wl9/Bz/y1NUbo+ZZ99iyF4GiY9p2aOI3qBtf9oG7PvUNlyvgytVZWS4320TWa9sSVLJd1UsphUsrBUsosKeXT5sefkFLONd+ullJeKqXsI6UcLaXc4e2Bt4bLR3end3w4D8xZx/7SVpTDDQyBsK6W++EJ4B9kK+j71kDyUFVv3SA4Ei5+W93es7R1gz9esG66Xat9dI2mPfHplaL2BAX48cbVI6iqbeCWD1dTU+9i/1Fn+PkpC8awXOqq4eAGSBnedN+wrhCVCvvXte09j3VqrQVd++gaTXvSqQQdoE9CJP+8bAg5+SU8OTev7Qe0Xlx0ME/VTk8e5njfboPhgK8LurXloiN0jaY96XSCDjA5qxu3nepG/9HmsF5ctG+12joT9KRBULTVtyNXG8tFe+gaTXvSKQUd4J6JfTmjfwJ/nZvHJyvaUGArOlXVRG8wdzUKi7Nkv9iTNBiQypbxVaxPVr584tJojkE6raD7+wleu2I4E/rG89AXuXy6Mr/lFzkiJk2tIC3bpyL05GG2E6LWdBustgd8eKGRtYhry0WjaVc6raADhAT6M+OqEYzLjOfBL9bxdc5e9w9ipC4WbYHCTY4nRBv3TYOQGDiQ27oBHw/oLBeNpsPo1IIOStTfvHoEg1OiefHHze4vOjLslc3fq0jdmX8OKnJPGuTbmS42Ebr20DWa9qTTCzooUb/6xHTyj1Sxek+xey+OSlHbjd+qbXOCDtBtCBza4LvNpWsrICAEhJ/20DWadkYLuplJAxMJCfTjqzVudjcKCoOwWKg4BJHJEJnU/P5Jg1SBL6Mnqa9RWwFB4aohiLZcNJp2RQu6mciQQCYOSOLbdfuorTe592LDdmkpOgdzpgu+a7vUVUJgOARH6ElRjaad0YJuxYXDkimurGPRFjdL+xoToykuCHpcJvgH++4Co8YIPVxH6BpNO6MF3YqxGfF0DQ/iS3ezXdyJ0P0DIHGAjwt6GARFaEHXaNoZLehWBPr7cd7gbvy84SBl1W6Ufk3oBwGhkNxMyqI1SYOV5XJsVRj2DHWVEBimLReNpgPQgm7HBcNSqKk3MW/9AddfNPQqmL7athJjcyQNguoS32xfV1uhonMdoWs07Y4WdDuGpsWQHhvGu0t2UV3nYjVG/wCISnb9TboNUdv9Oe4P8FhHWy4aTYehBd0OIQSPnjOAjfvLePiL3NZ3N2qOpMHKltix0PPH7mjqKtWEqLZcNJp2Rwu6AyYOSOTeiZl8uWYvby7yQq+OwBDVzm7Lj77no9dWqLRFHaFrNO2OFnQn3H5aH84Z1I2/zdvEgk2tbFnXHBkToXQPFG72/LEBjuyETd9559jOkNLWcqmv9t0VsRrNMYgWdCcIIfjHpYMZ0C2K6R+vYUehh6PNjDPVdut8zx7XYNnr8Nk0MLm5SKotNNSCbLBYLqCjdI2mHdGC3gxhQQG8cfUIAgP8uOmDVRyt8WC0GZ0KCQNh60/uv/aPVyH7neb3OXpQCWzl4daNrzUYtVsMywW8L+gmEyx4Do564SpKoznO0ILeAqldwnjtimHsLKrg3k9zMJk86HlnnqmaRleXuv6a8oPw81NK1JujwrzatdzN2jRtwRD0oDAVpYP3J0YPb4XfXoDNP3j3fTSa4wAt6C5wUu84Hj6rH/PzDvLfhds8d+CMM8FUD9sXuP6aVe+pvqVHdkBVM5UhjYi13I18+rZi1EIPCofgSHXb2xUXq8vUVpfq1Wi0oLvK9af0ZMrQZF76aQsrdx3xzEFTR6uGF1t/dG3/+lrIfhvC49X9fc3ksVcYgr6/bWN0B8NesbFcvCy0NearGy3oGk3Lgi6ESBNCLBBCbBBC5Akh7nSwzwQhRKkQIsf87wnvDLfjEELw7IWDSO0Sxt2zc9wrDeAM/wDoc7ry0V2ZvNzwtfLGJ/9N3TeaUttTX2uxccraKOhVxfDaaNi5uOV9a60jdLOge9tyaYzQy7z7PhrNcYArEXo9cK+UcgAwBrhNCDHAwX6LpZRDzf+e9ugojxEiggN4eepQ9pdW8+TXeZ45aMaZKpp2ZdXo8hkQ2wcGXgRde8FeJ4JeYVUtsq0R+qbvoGgzFKxoeV8bDz3C9jFvUaMFXaMxaFHQpZT7pZSrzbfLgY1AircHdqwyokcXbj+1D1+s2cvctR6YcOwzEfyD4Nf/A5NVqYGGevjxcfj1GZWrXpANe7Nh9M3g56cqO+5b4/iYFVYZH20V9A1zzcdxwYuvc5Tl4m3Lpdx2q9F0Ytzy0IUQ6cAwYLmDp08UQqwVQvwghBjo5PU3CSGyhRDZhYVu1hw/hrjjtD4M6x7DY1/mcvhoTdsOFh4LZ/8Dtv8Kv5gvbEwN8OXN8Me/YfE/4T+j4YMLVRegoZerfZKHQ9lelfViz1HzdxvatW2CXl2qxgWuCXqHWi5a0DUalwVdCBEBfA7cJaW0v75dDfSQUg4BXgW+cnQMKeWbUsqRUsqR8fHxrR1zhxPg78c/LhlMZW0DL/64pe0HHDENRv4ZlvwLcufA3Dtg/Rw440m4Z5PyzBMGwPgHLNkjKeZSvY6idMNy6Ta4bVkuW+arjJrQLi4KumG5hKtaNQjv56EbVku1tlw0GpcEXQgRiBLzWVLKL+yfl1KWSSmPmm9/DwQKIeI8OtJjjD4JkVxzYjqfrNxD3j438sidMfkFSBsDn18PObNgwsNwyt0QmQhjboHr58PJ0y37Jw1WjZgdTYwalku3IUrc62tbN6YNX0NkN2ULHXXDcgkKByHM9Vx02qJG014EtLSDEEIAbwMbpZQvOdknCTgopZRCiNGoE0U7LlHsGO48I4Ovcvby1NwNzL55DOqraiUBQXDZTJh1MfQ9B8Y/2Pz+wREQ19fxxOjRQuVjd+1tvn8QYsxdlQ5vV958WYGya6pLVOnfmB4Q3xfGPaBsoJqjsO1nGH4NBIaqfaVUQu2M2goQ/mpOwBijt4W2Rgv6McMPD6kgY/JzHT2STkuLgg6cDFwN5AohjFSMR4DuAFLKGcAlwC1CiHqgCviT9Erd2WOL6NBA7juzL498mct3ufs5d7AbNdEdEZkIf/nd9f1ThsOWeU2FtuIQRMSr6BqUXWII+vovYPN3KrsmaTCERCsvvniXKiewczFcOxd2LVbFtQZMUd2VGmpUCmNzTTxqKy3RObRPxcVqnYd+zLB7Cfj5d/QoOjUtCrqU8neg2dBTSvka8JqnBnU8MXVUGh8s283T32wAYPLAJAL822m9VvIwZc+U5kNMd8vjFYVq8VFkkrpvvfz/0AYVjV/5WdPj7VgIH/0J3jsXorqpY3Q/UUX4oLbNCXpdhWXJP5gbRXs7bdEs5LXlajJZC0rHUVOmrtA0HYZeKdpG/P0E/7hkMOHBAdz+0RpO/edCPli6i/qGdqhyaEyM2tsuRwshPMHSRcl6QvPQRjXB6oheE+CK2Spa3/4r9DtHCWRjpN9CxkxthXky1ExwpPezXKzzz3Vlx46lusy9ukQaj6MF3QNkpUTz8z3jmXHVCOIjgnn86zymvrmM/COV3n3jxCzwC2w6MWpYLqFd1fNl5gi9vlYVs0ro5/yYvcar6D2uLwy/Vj0Wkai2jlIkramtVIuKDIIivJ+HXl2mPiNo28XTFG6BBhdXREupTq41Zb7XtOU4Qgu6h/D3E0zOSuKLW0/mlT8NZcuBcs56ZTGfryrwThs7gIBgSBxoG6GbGlTJ3PAEtQApspslQj+yXRUDcxahG/QcC7evsFwBNFo3LUTodRWWBUWgLJf2iNCjzFcQWtA9R81RmHGymkB3hbpK9X+roVbNvWg6BC3oXmDK0BR+uGssA7pFce9na7l/zjqqal1sOO0u3QbDwTxLVFR5BKQJIhLU/cgkixAfUj4/Cf3de4+gcAiOsnjpzmhiuXg5bbGuWglIVKq6rwXdc1QWqe925VvKgmsJ63UAek1Ah6EF3Uukdgnj45vGMP30DOasKuDC/y5hV5EXxC1hAFQdsSwmMnLQw83LAGwEfaOatIrNcP99IhJd8NAr7SZFvZzlYgh4tFnQtZB4jqoStTXVwa/Ptry/9VyGrqvTYWhB9yL+foJ7Jmby7nWjOFBWzXmv/u650rsGRrRtRN9GHfRwc4QelWyxXA5thNjeqkm1uxuAh/sAACAASURBVEQmueCh22W5BEeaL8W9dHViCEd0iu19Tdsxau2njYHcz1TqanPYROh6YrSj0ILeDpzaN4Fv7ziF+Mhg/vzuStbv9eB/eMMPP7RRbSuK1NbacqkpU57ooY0Q38yEaHNYR/rOqLOzXAxx95btYghHlCHo2nLxGIagn/GkWqvwy1PN719j9X9aC3qHoQW9nUjtEsaHN5xAVGgg17yzgm2HPGRFhMdDWKwlQm+0XMy1coyUw+KdqstRSxOizohMUh56cxO8jiwX8J7tYkTkWtA9jyHoXdJh3H1q1fDORc731xH6MYEW9HYkOSaUD284AT8huOqt5RQUeyCtUQgl0kaEfvSQWnofEq3uG4K+4zdAuj8hahCRpLIXqkscP29qgPqqppYLeC/TxRARI99eWy6ew/idQ2Ng1I3qyqu5vq3WIq5/hw5DC3o70zMunA+uH01FbT3Xv5dNuSc6HyX0V4IupWWVqLH83hB0owxuWyJ0cO6jG/1EHVouXoqcjYg8NEaVFtYRuueoKoaAEFXHJzBEnTTLmqn/X6Mj9GMBLegdQP9uUbx+5Qi2FR7ljo/XtH1VaUJ/ZWuU5lsE3cDI0d69REXuXXu17j0MQXdWddG6FrqBt7sWGSISHGVelXocR4aLXoR8F7pCtRdVxapsskFkt+bnUKrLVGEu4a+zjToQLegdxCkZcTw9ZSALNxfyzHcb23Yw64nRo4csE6KghC4oQtklcZmqj2lriDAidGeCbrZVbCwXLze5qLYXdA9G6DXlbasl7w57V6mOVWs/bp/3c4WqEltBj0puvj9tTZn6DY73E+txjhb0DuTKE3pw/Sk9ee+PXXyyYk/rD2Rkrhza0DRCB0t03Vr/HFQlSHAucnWOInSzh+7NSdHAMHWSCo70bGT46zOqSFlbKT8I/8iAglXO91n6X7U1JiKd0Z5L6u0F3YjQnTUzry6D4Gg1d6Mtlw5DC3oH88jZ/TmlTxxPfpPH1oOtjDBDYyAyGQ46E3Sz7dIWQTcifacRutFP1JGH7q0IvVRF5wAhUZ6N0I+Ys4LamkO/b43KPNrrRNBLCyDvS3W7soU1Cl/eDHP+3LbxuEpVMYTEWO5HJatFRpVO2hxUl6rfICRKWy4diBb0DsbfT/DSZUMIDwrgjo/XUF1nEZBD5dXU1LsoKAn9IX+5Wq5tbbmAlaC3ckK08ThJzXjoVt2KDLxtudSUKwEBz1sulUUgGywLtVrL4W1qW+5kQnHFm4BUhdaai9Arj8D6z2H/2raNx1Uceejg/HPUlKnoPCRGR+gdiBb0Y4CEqBD+edkQNh0o57nvN7JxfxnTP17DmOd+4bp3V1LnyqRpQn8o2a1uh9sJujEx2tpFRQYRSe5ZLoFejtBryiwRuqcF3Vig1ZYm26CqW4LjDJGao7DqPeh/nmo20pygb/hKFb8yxuVtqorVlZ+BkRrqzEevNv8WwVHaQ+9AtKAfI0zom8CNY3syc+luznplMb9sPMhZWd34Y/thnnVl0tQ6+g63a+fa9xwYcoVqbNEWIhPds1z8/JSoe3NStDFC97CQGNZCWwW9yByhOxL0tR+raHbMbSoabk7Q15kbklSXuF7StrXUVas1BW5F6NpyORZoZcqDxhvcP6kfJZV1pHYJ49qTehATFkTStxt4+/edDEiO4rKRac5fbO2P21su3U9Q/9qKUYrXUW/RRsslwvbxYC8W6Kops9RxCY5S7+OJrkV1VZYxN5d77QrOInQpYdnrkDIC0kbDrkXqPetrVX9Za0ryYc8fqqpkWYGyX4xJam9gvajIICIBEC1H6H7+2nLpQHSEfgwRFODHPy4dwp1nZBATpv6oHz6rH6f0ieOxL9ezek8zEVx8Xxo7BdpbLp4iIlFFbo4i4UZBD7N93JsVF6vtLBewfa/qstZNalrbGm2J0KvLVLkEv0B1HOsslYpCVZ9+0KXq5GhEw1UOJkbXf662o65X20ov2y7GlYJ1hO4fqETdUYRuNLcIsbJcnGXDlO1TZQQ0XkEL+jFOgL8fr10xjKToEP7ywSoOlTlpHhAUrupuCL/m+362Beum0/Y4WikKKkL36qSoucRBY5kBs49uMsGrw2HxS+4f11ow25KLbkyIpo5S34912QSjxrix0CvU/Js5sl1y50DKSHUc8L6PbpTOtRZ0UL+/owi99qiqwR9iTltEOl8dvOx1+Phy3dXIS2hBPw6ICQvizWtGcLSmnr98uMom86XBJDGZzH8cCQMgLM57jZLtc9FNDZY/zNoKCAht+t7eitAb6lV1R/sI3RD08v0qCl4/x/1jG4LpF9A2y8UQ9J7j1Nb6WIagd0lXW0M87VMXD22Eg7kqkjfmRjoiQgfbUszWWC/wMuY0nPnoFYUqE8vbzcM7KVrQjxP6JUXxz0uHsHpPCX/9Oo/qugbeXbKTk/72C6Oe/Zl3l+ykduz9cO7L3huEsVp0/ecw+2p4LhkWPq8eq61oareASnUsLfD8WAzbJyTKdmsIiSGYhZvg8Hb3jm0Ieny/tlkuh7epK6b0k9V96+i22JyRFNNdbcOcROi5c9QxBl6oTtYAFU5ywT2FMQbrPHQwz6E4ytax+i2ME6wzH92YbNaZMF6hRUEXQqQJIRYIITYIIfKEEHc62EcIIf4thNgmhFgnhBjuneF2bs4a1I3bTu3NJyvzGf3szzz1zQZ6dA0nMzGSp77ZwGmzivm6Zpj3ephGJgECVr+vct5jesDS/6iosq7SkqZoTWwGlOxRmROexLqOi/XWiNCNFE6Azd+7d2wjAk4a1Pxy960/w4t9neeGF21V35ERhZfttTxXvEsJZGCouu/MQ9/2M/Q4WV0dNUbxHRWhd1PP1VXZPt4YoUdbLDBngm1cgeiJU6/gSpZLPXCvlHK1ECISWCWE+ElKucFqn7OADPO/E4DXzVuNh7lnYl/2FldxuKKW207tw5hesUgpWby1iBfmbeLOT3KYs6qAZy7IokesA4FtCyFRcPnHyt7ofqKyA2acDCv+17RbkUFcBiDVqsvENi5ssqZRRCJtt4aQFO8GhKpfs+l7OOkO149dUaQmMuMyVDqes8+24Su10OqjqXDDL5aMG4PDWyG2j/nKRthG+8W7LEIPzj30sn3Q9yx12z9Aiayz1ZqeorpEXRUYJ0mDSHMuevl+2yJv1hG6Ybk5s1yMsWtB9wotRuhSyv1SytXm2+XARsDufy5TgJlSsQyIEUJ08/hoNfj7Cf71p2F8cP0JjOkVC4AQgnGZ8cy9/RT+b8pAcvaUcObLi3jjt+2ej9b7ngXpp6g/3KQsyJwMy19X3qgjyyW2j9oWbfHsOOwtF3sPvWS38nwHTIH8Ze7ZFBVFqnxCo4A5mRjduQi6DVGTvh9NtV3YZDIpqycuQ6Uhhsc3jdCtBT0oXJ1ErD30hnr1vRq1eEDZLl6fFDUv+/ezkwdjgZr9VYshzsZKUevHmhxbR+jexC0PXQiRDgwDlts9lQLkW90voKnoI4S4SQiRLYTILiwsdG+kmhbx9xNcfWI6P987ngl943n+h0088XWeZdLUG4y9VwnAnqWOo1hD0I18bE9hiGcTy8UqQo/pAf3OVhkYW+e7fuzKIgiPtRIwB75x8W510hh6JVz2niqM9tl1ljTJ8v3KhjI+v3U98foaJe7Wgi6E8tGtI/SKQkDaCnp4nPcjdPtVogbWEbo1hjgHRzX9HaxpqLPsqxcfeQWXBV0IEQF8DtwlpWzVryGlfFNKOVJKOTI+Pr7lF2haRWJUCDOuGsHN43rxwbLd3PfZ2rbXXHdG2mhIH6tuO/LQgyOUEBgrJj2FIQiGZ2ssaDKE3oiAuw1VLeo2fWd57f51UGoVLdtTUaQiYWcCBrBrsdqmj4U+Z8BZL8C2nyyFtowTWKOgp1gi25J8QDZduRva1dZDN943wjpCj22fCN3ePwfnJzjrq6XGyWkHna2sT1bOOl9p2oRLgi6ECESJ+Swp5RcOdtkLWC9jTDU/pukghBA8dFY/7jszky/W7OXmD1axs8hLqWJj71FbR5YLQFwfL0TodpOifn6WrkX1NUoMu/RQkW/fs1THpupSmP8ovDEWvpnu/NiVZsvFEDBHgr5zkRJ9Y4XuyOvVBPAf/1apnEXmzxuXobZR3SyWi33KokFoF0sOOKhFSWC7KjQ8rh0mRUscC3pwlFpn0CRCL1ONLQLDICBYdTpyFIFb20nacvEKrmS5COBtYKOU0tkqjbnANeZslzFAqZSyjUUwNG1FCMHtp2Xw1PkDWbytiNP+uZBbZ61i5a4jVNTUe+6Nep0KAy+yROr2xGaoCN2Tfn7jZX6k5TGjuYJ9BNz3LGV/vDYKlr4G0Wmwa4laZu+IiiIlnEbJYHvPWEol6D3HWUog+PnBSberjJddi5V/HhhuWYwVlayi0tpK1bAbmgp6WFdb0TO8+wg7D73yiPOVmJ7AWYQuhHlxkYMIPSTK8l04q6tjbRXptEWv4EqWy8nA1UCuECLH/NgjQHcAKeUM4HvgbGAbUAlc5/mhalrLtSelc9agJN5dsosPl+7m+1wlFHERQfRLiuL5iwaR1tVJdO0KQsCl7zp/3sgWqShsWmemtdSUqZZ6gSGWx4zCUCW71P0uZkFPH6cEytQAl89WVQtnXwkFKy054gZ11WohVJiacHaYe314u4pSjQVDBoP/pBpjLPk3ICG2t1VvVyv7pmS3imIj7OqxhMbY2hLlBwBh+52Fx6myvtUl3lsRbF8L3ZqoZMcRumF9gfMmF1U6Qvc2LQq6lPJ3GouEON1HArd5alAaz5MQGcKDk/tx64Te/LalkN2HK9lzuJJ5eQf405vL+OSmMS2KeoNJ8vJPW5g4IJEhaU7+4B0Ra7YdirZ6UNDLm6bVGSV0GxftmAU9IAhuXKCEJqyrshSEn4qy7QXdsDOMVZlR3Zpmuez8TW3tBT0wBEbfDAueUfZP5pmW5xrLz+5VlktMj6ZZJPYe+tEDahz+gZbHGhcXFXlH0E0mJbaOInRQJ7g9y2wfs240As4rLhoRemC4FnQvoVeKdjIiQwI5d3Ayt53ahxcuGcysG07gaE09f3pzGflHKpt97bfr9vHagm385cNVlFa5UcLV8JFd8dELsuHTa1vOgrAunWtgCHrJbhW9R1plznbtaRHA0BiVbmgIszXGhKPR9SnSQS/NnYvUJKejhtujrldecm255UQGan9Qx7JPWTQI7aJ6vxoLd8oP2totoLJvwHs+ek0pIJ0LepSDVnQ1LkbohqB3SdeC7iW0oHdyslKibUR91W7HFR3rG0y88vNWUmJCOVRew1Pf5Ln+JtFpymIockHQV7ypFux8e3fznrt1cwuDxgh9l1pSbx8BW9NzvLJc7GuKGIJuRMKRSbYCZjLBrt9t/XNrwrrCsKvVbSPDBawyRPaqKwhHgm6ccAwfvXy/bcoiWKwgb2W6OFslahBpbkVnY5/Y/RZOPfQj6mQXmXh8py0WbYWZUzzbUMVDaEHXNIp6g0ly8et/cM+nOU2qOs5du48dRRU8fm5/bpvQmy9W72XeehcrEfr5QdfelmJVzmiogy3zlGitnwNrPnC+r8MI3SwkRg56c/Qcp7z0PUttH29iudj10izcqPaxt1usOflOteDKep+gcBW5HsxTY+ziYHz2y/+PHmxa9zzMywW6GgXdmYfuIHWxxu63CIlyEqEfUb+tO42k62thyStqMvlYYfsC2LEQCj28WM4DaEHXAErUf7l3PLdO6M23a/dz2j9/Y/bKPUgpqWsw8covWxmYHMWkgUncfloGWSlRPPplLkVHa1x7g7g+thG6ydS0vsvuJeoP/dx/qQj6+wdUeQFHOIzQoyyWiyPBtKb7GLUyc4ed7dIYoVtNioJlItCo5e0sowdUCYArZjcV46gU2P2Huu3QcrFa/m8y9zNtYrl4uUCXs9K5Bo5y8x1OijqIwKuOqOMGOxF8R+xYAD89AbmfurZ/e1BqXkPp7fTRVqAFXdNIeHAAD0zux493j2NwajQPfp7L7R+t4f0/drH7cCV3n5GJEIKgAD9eumwo5TX1rrXHA+UnF++ypAp+dw+8NtI28tr0vSrB2+cMuOh/alHSZ9Nsc7MNnE2K1h5VgthShB4UrhZF7Vxk+3iluY6LIVDWgm4yqR6gqaMhppnuUc6wzphx5qGDimQrzE2q7S2XgGA14er1CL0ZDx0sEbrJ1PTkGhytGqHYp4VWHrZE6K6mLRZuVtstP7q2f3tgCHp79Xd1Ay3omiakx4Xz4fUn8ODkfszPO8Az321kSGo0p/e3ZKhkJkZywyk9+XLNXnILXIi24jKUQBXvgn05ShhL89UWlF++6TvofZpaoBSZCBe/pVIEZ57fNCJ1Nilq0FKEDsoS2b+26XL78DiLP24tYNt+VkXGTri55WM7wsh0AccnHOsSukfNdpa9oIOaGPXW8v+WBD0iEZtCY7XlgLSzXJxUXKw8oj5jSLR58teFCpxFZkHfscCzFTs3fgNrZ7futUY5aB2ha44X/PwEt0zozZxbTuLkPrE8cd4AhN0k4C0TehMbHsSz329ouQhYrFWmy4+PqT/s1NGw5F8qq2P/WtUvs985ltf0mqCqOxZuhvfOtmqs4SAqBFtRcaUhds/xgFSTnAYVhy0+NdgK2PIZygIZMKXlYzvCEPTweHX1YY+1h+5oUZFBcwW6TKa2NY8wroac5aH7B6orjSM71H3r5hYGjcv/7U701hE6uBalF25RV211lba/U1uQEuY/otJLW4Mh6BXHXj0qLeiaZhmaFsOsG8YwokfTnOfIkEDuPCODZTuO8MvGQwDUNZh4/49d/JhnN2EaZ874+ONVtZJywsNw+hNq4m/V+6pmufBTk4nWZEyEKz9Tqz/fmaw89dqjNIkKwS5CT2/5w6WMUFkX1rZLZZHFpwZLL82di2H7Lyot0Tov3B0MQXc2tsBQJV5VxRZBd9QMurnl/8tnwL8GtX4SsbpE5YnbN6q2pvsJaqWt0UsUbH8LR00uGurVsUO7WgS9JR9dShWhZ12kfqct89z/PI4o3Kxq9Jfscb89Yn2t5bfxdqORVqAFXdMmLh/dnV5x4Tz3w0ZW7jrCea/+zl/n5vGXD1cxb73VxFlItGpevWcpxPWFEddBz7GqecPvL0PeV6rGupFnbU3PcXDNV8o3f3OCOimArYBb3w+Ocm4ZWBMQpN7fumlxhZ2gg7I99vyhcttHTGv5uM4wctGbO9mEdoHKYksdF/vVpGCO0J2IyfZfVSRsFA9zF2fL/q1JH6vmAo7saFokzfq2dQRuFOOyjtBbSl2sKFSinzRYXa1tne+Z8hHWlTcNj95VyvYC5jFoy0XjawT6+/HQWf3YUVjBpTOWUlJZx6uXD2NoWgzTP85h8Vary1JjgdGkZ1WzBoAJDym/uGizrd1iT9pouHWpqsW+6O/qMUdZLqDsFkc54o7InKSEycjAMSotWmNkdgy8qG0rXY0J1ubsIKOEbvl+Fc0GBDfdJzxWiYm9uEmpcusBttiVC66vhW2/tDxGVwTdSMfcuciqSJq1oDvoK2p4/mHWEXoLFRcNsY3LUL9TyR7VUrCtbJlvyWIqdHFS38CYEA0I0ZOiGt9k4oBErjihO9ef0pOf7hnHeUOSeXfaaHrFh3PTzFX8sc38H3/I5WppfMZEy4vTx0L3k9Ttvmc3/0YRCXDFZzD5byraTRpk+7wh6K5MiBpkTlLbLfNUlcba8qZXCcbE6Ak3uX5cR3TtqVaX2pcbsCa0i9lDP+h4QhTUCaehtunClsPblUj6B8PWH20Ff9l/4cOLnKeBGjirhW6N0YVp12Kr5hYOJkWtLRVjsVSYG5aLMSEa3xcyzGUU2mq7VBWr0gXDr1HfU0vfhz2Gf540WEfoGt9ECMFzFw7i8XMHEBmi/OXosEBmXj+axKhgrnhrOWe9spi3K0+hePwz9i+G816Bc/6pBK8l/PxgzC1wzwZLxG9gWC6uTIgaxHSHxCzYPK/psn+DYVcpvz9lhOvHdURQOExfozJ5nBHaxZLl4shuAYslZC8oRnQ+8joVSRpiJaXqAwtqYVNzVJW0LOhCKLtsp5Wg268UBVvLpTFCj22+CYY1RVtVtcuoFDX/kDS46ZWHu2z7RWVb9T0b4jNbL+jdBmsPXdO5SIgMYe4dqi1eoL/g/77dwBkv/UZOvt2ldnwmjLqh7W8YFqvEOG2Ue6/LnKS8faPWjL3lkjJCdWZqD4wSuuUHbGvR2OxjLP+3E5SClSpH3eifanjFuxZbslJaagXoiuUC6sqq4hDsXaXuN5kUFXYRunms7kyKFm5WJ23DPsucrJqTW5cYdpetP6rvL2UEJAxwX9BL9qgTbVQy1FU0bZjdwWhB13iVqJBArj4xnbm3n8K3d5xCWLA/l7+5jF82qkm/suo6Pli6iyfn5rFw8yHq2tJZKTAE7tsKAy5w73WZZ6mobZ15NaL9pGh7Ylgujpb9Gzhb/r83G1KGQ3SqsqO2/qQeX/WeEtHotOY9aCldF/Se5pWym39Qk8UBVmWM/fzU1ZK1h26UMwiLVVcqwt8Fy2WLavJtkDlZtRPc/mvL43OEqUF9J30mqp648f3U5K6jhWvOKC1Q36911ctjCFfqoWs0HiErJZovbjmZP7+3khtnZnN6/0QWby2kus5EkL8f7/2xi+jQQM4fksyj5/QnJNDf/TdxdTLUmpTh6g/UaB9nH6G3J6FdVY0ZcJyDDhaP31pMaivhwHo45W51P+NM+P1fylff+I3KKirNd5zVYTKp762uChpqnOegW9OlJ0SlqrUDYXFNv3f75f2Vh5XoG12tnJXYNagpVxkl1oKePFSdmHYshEGXtDxGewqy1YnFmDdJGKC2hZtUKQhXKM1XFl1jCYbC1q0a9hI6Qte0K/GRwXxy0xjGZ8bzx7YiLhyWytzbT2bdk2fyv2tGcmrfeD5YtpvbP1rdtmjdHfz81R95nTl3u6MjdIPmJkXBNkLfn6OuMlLNdlPGJHX/q1vUBOqIa9Xk4uHtqgiaQfEueD4Fnu4K/+jTdAzOMHx0aLoeAJou768stlhFxvPNRehG1lF8X8tjfv4qw2bHb61LX9w6X10ZGHMYCf3U1lXbRcqmEbq3G3a7iY7QNe1OeHAA70wbRb1JEuhviSkmDkhk4oBERvTowuNf53HfZ2t56bKh+Pu1Iuq2I/9IJV3DgwgPdvJfPnMS5MyyrePSEVg3rXAm6EHhTdPmjAnR1JGWbWgX5TmnjoLEgao5tqkOjuxU8xagot26Shhzq1rYZWpQLftcIX0srP24afooNK24WHnY9rO1KOhmr986Qge1unfjN6qNn6N69M2x7WcViRuTvtHd1SIqVwW98rAqWRCdZhWhN2O5mEzNl3D2AjpC13QIQggbMbfm6hPTeWByX77O2cdjX61vuaxAMxw+WsPDX+Qy/h8LuGTGUkornTTm6HWqEvOw2NbZNp7COjp2luUihLm3qFV0WLBS2SCG0Pj5qyJnAMOvVVsj2i2ysl3yV6jPPOk5tT7grL85P5HY01KEbl0jp/KwpZqk8Xxzgl64GfwCmop2rwlqu2Oh7eNVJepk5IyacjiQq9YxGPj5qe/E1Vz0kj1qG5PmPNPIoPII/K1727Ny3EQLuuaY5NYJfbhlQm8+XrGHF+bZ+r5FR2t4/vuNPPH1ep7+ZgN/n7eJ7YW2S7jrGky8tXgHE15cyGfZ+VwwNIXth45y7bsrOOqoQXZIlLoUdyeH3RuEOo/Qy6rrKKk0VzC0L9BVkG2xWwxGTFNRdNZF6r4R7VpPjOYvh7QTWncSi+muavQ4ysZJzFKRryHqVUdsLRf7JhhHdqpyyYbIF21RYm5fZiG2j0pjtC57fLRQlTtY/obzsRZkqwnVtBNsH7fPdJHSuZ1jpCxGp6rx+wU6j9AP5Ko1DdarkNsBbblojlkemNSX0qo6Zvy2nS5hgdw8vjcb9pVx48xsDpZVExkSQH2DpLKugf8t3sGNY3tx+2l9yN5VzFPf5LG9sILxmfE8fm5/+iREMjkriVtmreb691by3nWjCQ2ym3S96E1bf7kjMCL0kGhV28WKm2Zmc6i8hnl3jiMoLE5VgGyoVxkx5fubCnr6KTDtW8v94AhzpovZzqg4rJqODLuq9eO95itVf8aezEmw+EWVkZJ1sQPLJcY2Qt/wNax4Q0XLV37eNMPFQAhlu2yZZ7E0VryhTg75y+DEWx2PM3+5spTsv6OEfpDzoaXkw/xHYd0nMP5BGPln2xNKo6CnqXE0V1PHsIz2rnb8vJfQgq45ZhFC8H9TsiirquP5HzZRUFzF56sLiAoJ5MtbT2ZQqvK6C8treP6Hjfx34XY+XLabsup60mPDeGfaSE7rZ7EtzhyYxEuXDeGu2Tlc/PofPHn+QEb3tBKZlhbUtAeGoNtluOw+XMGyHSr176Plu5mWPEwJ5qvDLFGn4Z83R1ymJUIvWKG29lGrO0SnOn48ZYT6LFt/UmmkVSXNT4oWbVHpjzsXwZc3q7z5fuc6Pnav8bD2IziYqzphrfifery5RVN7lkHCwKb2UEJ/tT20UWX4LPuPyt754QEV8U/+m6XZd2m+8tyN36i5mjpGd64DuarsQnPFzjyItlw0xzT+foKXLhvK+EyV/ZKZGMnc2y1iDipz5qXLhvLpzScyumcsD0zuy/y7x9mIucGUoSnMuGoExZW1XPbGUm77aDWLtxaydPthVuw8wv7SDl4oEhCkVkfa5aB/uWYvQsDA5Che+WUrZSfeD1M/VHVmcj9TUXJiVsvHj++nMkhMJuWf+wVA8jDPfw7Dw9/6k3khkGzqodceVVcYoDzz7mPg9L9C3hcqddM6w8WanuPVdsdvqk1hdYnKLT+83XHp4IZ6NcfQ3cGJK94s6HuWwte3q+/njlVw+Wz1GT6eCkVmcS7NVycww54yauo4wsjSaaiBQ3Ynmk+uhDWzHL+ujbQYqI7JcAAAEz1JREFUoQsh3gHOBQ5JKZv8jxFCTAC+BnaaH/pCSvm0Jwep6dwEBfgx46oR/LjhAJMGJjnNTx/ds6ttxO2ESQOTGJsRxxu/7eCNRdv5bp2lKqSfUNk2007qyYDkKJZsK2Lh5kPsL61mWPcujE7vyoDkKBpMktoGExHBAUSHtrKcrjNiuqvI04yUki9W7+XEXrE8cnZ/zn31d15ftIsHJ58H/c+DglWqQ5ArUWB8ptq3dI8S9G5Dmlg7HiPjTHWyMRYC2UToVsv/Q7uoCH3wVJVHX7YPVv6vaa0eg6huqmKn0XCk+0mq3MG2n1SkbX+lcihPnTzSHOSaRyWrwmK/vaDuX/6JWqDWd7Jan/CvQaoa6AX/USWcrXPOw+JU/1pHFG1V9k7BSmW7GCfNIztg07fNtzBsA65YLu8BrwEzm9lnsZTSyfWRRtN2QoP8mTI0xWPHCwsK4O6JmVw5pjs7CiswSUmDSbJ0+2E+XrGH+XkHG/eNDAkgJSaUV3/d2mS+LDTQn8/+ciJZKR5MdbzqC8sCHGDV7mL2HKlk+ukZZKVEc+GwFN75fSdXj+lBckwopLpRYybenHt9ME8t2x95nefGbU/v0wGhUhuhadoiKNulvkYJe1ymin7P+rsqBWHkiTui13hY8aa6ffaLln0Prm8q6HuWq62jCF0I9dr85XDqY2rxkkFEgppYXvkWjH9AeejWz4c7aTRSW6mi+WFXqauGfauB69VzRis9w8bxMC0KupRykRAi3SvvrtF0MAmRISREWpatj82IZ/rpGczN2cfekipOyYhjWFoMAf5+lFXXsXp3MTsKKwj0V2mXL/64hUe+zOXLW0/2SL48YKnuaOaLNXsJDfRncpby1e89M5PvcvfzyJe5PHfhICXqrmJMNObOUZG6/SShJwmPVeJqpBg6E/Rqc5Rr5Mb7+TUv5qDSF1e8qU5QGWcqYQ6OUqtl7clfpqypaCcrOgdMUXaQscrWmpOmw8q3VQRfWWQ7ZxAepzJZ6mtsyxwf2Q5I1dQlZbjtxOiWeerqwt0cehfx1KToiUKItcA+4D4pZQsl3TSaY5eQQH8uG9X0jz8qJJAJfROYYGXthgUHMP3jNcxcuovrTnahWqSbVNc18O3afUzOSiLCvCgqtUsYD0zqy/M/bGLc3xdwzuBuXHdyT4akRjdpE9iEsK6qgNkmc/ZLWyZEXSFjkmXRk/2kKKjI3PCb45x45o5IH6uqap76iGXxTuJAFaHbs2e5is6dfTcn3qb+OSI6BYZeYalWGd3d8px1PZdoq6vHxs+TCcnDleVUW6HSJnf9rqqFeglPTIquBnpIKYcArwJfOdtRCHGTECJbCJFdWHjs9ePTaNzlvMHdGJ8Zz4vzN7OvpPkJ1R2FRznrlcW89ONmautdK2vw66ZDlFXXc+EwW7vphrG9+O3+CVx7Ujo/bzjIBf9ZwoQXF/L3eZvI21fa/GKs+H6qHEBUqq0QeQPr2vfWk6LWbeoKN6v7ri5oAuXB37XOtr9r4kBlJVl/9tICVW/GkX/uKqfcrUoGQNMIHZpOjBoZLl17q2wfaVI9c7cvUCt1jVoyXqDNgi6lLJNSHjXf/h4IFEI4LIYhpXxTSjlSSjkyPj7e0S4azXGFEIJnLsiiQUr+OjfPqZAeKqvmmndWsLPoKP/+dRsX/ncJmw40Xw/8UFk1b/y2nYTIYE7u0/RPKrVLGI+fO4Clj5zOCxcPonvXMN5YtINz/v07E19exL9/2crOIgdZH4btkjba7c/rNkmD1YpX/2BVssDA2nIp2mzxz9tCYpaK+I0VnaDSFcGxf+4qXXvCoEvVbftJUWjqoxdtUfZOUJiyXEDNV2yZrz63F6+K2my5CCGSgINSSimEGI06SRxbFWs0Gi+S1jWMu8/I5PkfNnHX7ByeuSCrsdEHqBWe1767kiMVtcy+6UQOlFXz6Je5nP/qEs4alMT4zHjGZsQTH6l8WCkln60q4JlvN1BTb+JvFw9q1p+PCglk6qjuTB3VnSMVtXyfu5+5a/fx0k9beOmnLaR2CeWk3rGc2jeByVlJCGNi1Nt2Cyg7pP/5sHuJrWBb9xUt3NJ80w9XMdI2D+ZZVvzmL1e544lOMmZc5cxnVKepGCvLpTFCt5O7oq2W5isRCepKaO8q1Vi7zxmtbzLuAq6kLX4MTADihBAFwF+BQAAp5QzgEuAWIUQ9UAX8Sbal+IZGcxxy49he1Nab+NcvW1m9p5h/XjqUsCB/th06yofLdrP1YDlvTxvFkLQYhgAje3ThxR8389OGg3ydsw9Q2TThQQH4+wn2llQxKr0LL1w8mF7xES6Po2t4EFeN6cFVY3qwr6SKnzYc5I/tRczPO8in2QVMPz2De7LGqOJenhBRV5j0nMrHtsboLlWar7ozxTtYFeouiQMAoXz0fmcr62XnIpUF5N/G2DUiXrWtsybMQRljKZXlknal5bGU4bDpe/UdZE5u2zhawJUsl8tbeP41VFqjRtNp8fMT3HF6Bif1iWX6xzlc9sbSxueCA/z452VDGJ9psRljI4J5/qLBPHuBZMP+MhZvLeJQeTWVNQ1U1NZz66m9uXxUd/zakDmTHBPKtSelc+1J6TSYJA9/sY5//7KV+IiBXP3ogfYrQhYQ1DRH3s9f+eb55tWq7kyIOiMoXGWPHMhV9zd8rVbFGh2cPE1IjPLWrT308v0q5926PWLKcNg4V5UeMAqmeQm99F+j8SAjenTl+zvH8nXOXmLDg8lIjCA9NpygAMfTVX5+gqyUaM/msTvA30/1fT1SUcsTc/OIjQjm7EFOWty1FyHRcGCduu1sVai7GBOj9bXwy1Oq+NaQZmPS1uPn1zQXvTHDxUrQk80+etoJtqmb3hiSV4+u0XRCokMDuebEdM4Z3I3MxEinYt7eBPj78erlwxnRvQt3fZLDgk2HXH7tnFUFLU7iuk1ItMq28Q9yr7F3cyQNUqsxl/1HbSc+ra4GvEWYvaCbi3LFWgv6MFXOwd3WiK3g2PifptFo2oXQIH/evnYUmUkR3PRBNj/mHWjxNV+uKeC+z9ZyyetLWbbDeb5DbkEpP284SEFxpWs17I3Uxa69W+Vxm0wO3iNxICDh12dUrrqXLY4m9VwOb1OTsFHJlsdCouCuXBh9k3fHghZ0jabTER0WyKwbxjAwOZpbZ63m23X7nO67+3AFj3+Vx/DuMXSLDuGad1bw04aDNvuszS9h2rsrOO+137lhZjanvLCAwU/9yKNf5joWXQMj06UVE6Lr95Yy5Okfufrt5azNt2rybGS6mOpVdO7teYImEfpWtULU/n3DurZL9yLtoWs0nZDo0EA+vOEE/vzuSqZ/vIa8fWVMPy3DpkZ8XYOJOz/JQQh49YrhhAX6M+29lfzlw1Wc1DuWmjoTZdV1bDpQTkxYIA9O7sfonl3YuL+cFTuPMGv5HmLDg7jnTCf+uCHobk6IFpbXcNPMbEIC/Vm/t5Qp/1nCGf0TiY8MYvP+MmbQhU0hQyk8kMDZ8Q1N6957Evua6EVb2ye/3wla0DWaTkpEcADv/XkUT3ydx+sLtzM3Zx9/PW8AmYmRHK2p5/PVBeTkl/DaFcNIMdeLmXXDCTz+1Xp2FlUQGuhPt+gQzh3cjWtPSm/MvR/RoytXntCd4AA//v3rNvomRXHOYAcTsI0RuuuCXlPfwM0fZHOkspY5fzmJHrFhvLtkF/9bvIMAP0FGYiRv9nuPRfl1bPlsLU9+k8ddZ2Ry/SmulWUoraxj5+EK18oogIrQq0tVY5SGOktRrg5CC7pG04kJCwrgxUuHcNnINB77KpebPlhl8/xlI1M5d7DFD44IDuDlqUPtD9MEIQTPXJjF9sKj3PfZWkKD/CitqmNtfil7jlRSU9/AhcVlXAKsqoxnuJQIIaitN/H56gJ+2XiQ+yb1pV+SpSGFySR59Mv1rN5Twn+uGN6YGTT99AxuP7UPQtAowlJKlu88wozftvN/327g8NEa7p/Ut1mRNpkkN87MZsWuI4xK78JdZ2RyUu/YZl+zsMDEBODH7z7lzMrvAdlyYTEvIjpqDdDIkSNldnZ2h7y3RqNpSl2DiXnrD1BvMhEeFEBMWBAjenRpUxXJQ+XVTHltCftLqwFVbrhXfDghgf5MqFnIlSWvc2L1vxnQPYEz+icya9lu9pVWE+TvR4C/4OWpQ5k0MIn8I5U8MGcdS3ccVoujJrrmuzeYJI99lcvHK/K55sQePHneQKe5/TOX7uKJr/O4dEQqi7cWcaCsmp5x4TSYJOXVdQQH+HPPxEwuGZGKn5/gtV+3kvfzB7we9Ir6/gLCCTzpVpjwsFcza4QQq6SUDttTaUHXaDReZUfhUdbsKSErJZo+CRE2J4ia2lo+W72f1xduZ29JFSN6dOHO0zPITIzk5g+yWVtQykXDU5i/XmXjPHbu/7d397FV1Xccx9+fVQoWJrRVGGs7i9rIsBEx6CBOfNgyQZeBiTOaRYjB+I+JzCzbNPwlLlu2GeeWGDMnKm6LmDE2mYksikQ0TEDEKLagVB4K6QMEyoNCH+x3f5wf5lLbldJ7Obu/830lN73n3Nue37ff9tOe3z3n3CnccVXN6U2HBGbGr17ZxlPrPuGaSyq559qLuK7uglOCvfngZ9z0+Dqm11aw7O6r6Ozp5cVNzby14wCjS0v46qgRNLQcYfPuQ1xdW8HUmrH86c2dLKwvYfHhh3mpcxpL9l/HL+6c1f/0Uh55oDvn/q919fSyr+M4tZVlX4T1ie7PeWjlB/xjS/JuTb+57XJqKsoG+Ur9MzOeW7+LJ9Y2ceBYJ9+oKOP26dV877KvUTd+DHct3ciWPYf49wOzqC7vfxu9vcaKzXv55SuNdHzWza3Tqnj0h1Mp+Yo43vU585/ZwJY9HSy+5ZssmFn7xR+MTbsO8tvV26kcU8oNl47n+skXnHIN/qHyQHfOFSUz46O2Y9SNHzOsyyCc1NXTy+oPW/nLf3azcVfyptsTzhtJ25FOHplXz10zBj/B6eCnXaxvOsCc+omn7G0cPdHNouXv8fq2dr41qYJH5tWzfGMzz67fycTzRtFr0HokmXq674aL+elNZzbX7oHunHN9tB4+wWuNbbza0EZ52Qgeu/2KYf/ROHmlzCX/auBYZ/IG2PNnXsjPZ0+mrLSExpajrN3ezuXVY7m27swuIe6B7pxzZ9G+juP88Y0m5tRPZObFlYN/whD8r0D3wxadcy7Pqsady5K59Wd9u37qv3PORcID3TnnIuGB7pxzkfBAd865SHigO+dcJDzQnXMuEh7ozjkXCQ9055yLRGpnikraD+w+w08/Hzgw6LPik8W6s1gzZLPuLNYMQ6/7QjPr97oBqQX6cEh6Z6BTX2OWxbqzWDNks+4s1gz5rdunXJxzLhIe6M45F4liDfSn0h5ASrJYdxZrhmzWncWaIY91F+UcunPOuS8r1v/QnXPO9VF0gS5ptqTtknZIejDt8RSCpBpJayU1SPpQ0qKwvkLSq5I+Dh/L0x5rIUgqkbRF0stheZKkDaHnL0oqTXuM+SRpnKQVkrZJapQ0Mwu9lvRA+PneKukFSaNi7LWkZyS1S9qas67f/irxh1D/+5KuHMq2iirQJZUATwBzgCnAnZKmpDuqgugBfmJmU4AZwH2hzgeBNWZWB6wJyzFaBDTmLP8a+J2ZXQIcAhamMqrC+T2w2swmA1NJao+615KqgPuB6WZWD5QAdxBnr58DZvdZN1B/5wB14XYv8ORQNlRUgQ5cDewws0/MrAtYDsxNeUx5Z2YtZvZuuH+U5Be8iqTWZeFpy4B56YywcCRVA7cAT4dlATcCK8JToqpb0lhgFrAUwMy6zKyDDPSa5B3TzpV0DlAGtBBhr81sHXCwz+qB+jsXeN4SbwPjJE083W0VW6BXAc05y3vDumhJqgWmARuACWbWEh5qBSakNKxCehz4GdAbliuBDjPrCcux9XwSsB94NkwzPS1pNJH32sz2AY8Ce0iC/DCwmbh7nWug/g4r44ot0DNF0hjg78CPzexI7mOWHJ4U1SFKkr4PtJvZ5rTHchadA1wJPGlm04BP6TO9Emmvy0n+G50EfB0YzZenJTIhn/0ttkDfB9TkLFeHddGRNIIkzP9qZivD6raTu1/hY3ta4yuQa4AfSNpFMp12I8n88riwWw7x9XwvsNfMNoTlFSQBH3uvvwvsNLP9ZtYNrCTpf8y9zjVQf4eVccUW6JuAuvBKeCnJiyirUh5T3oV546VAo5k9lvPQKmBBuL8AeOlsj62QzOwhM6s2s1qS3r5uZj8C1gK3hadFVbeZtQLNki4Nq74DNBB5r0mmWmZIKgs/7yfrjrbXfQzU31XA/HC0ywzgcM7UzODMrKhuwM3AR0ATsDjt8RSoxm+T7IK9D7wXbjeTzCevAT4GXgMq0h5rAb8H1wMvh/sXARuBHcDfgJFpjy/PtV4BvBP6/U+gPAu9Bh4GtgFbgT8DI2PsNfACyesE3SR7ZAsH6i8gkiP5moAPSI4COu1t+ZmizjkXiWKbcnHOOTcAD3TnnIuEB7pzzkXCA9055yLhge6cc5HwQHfOuUh4oDvnXCQ80J1zLhL/BTHwAWwUv8iIAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loss =  1.2451868057250977 , val_loss =  1.55964195728302\n",
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r135/135 [==============================] - 4s 31ms/step - loss: 1.2452 - acc: 0.8736 - val_loss: 1.5596 - val_acc: 0.7958\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(loss=\"sparse_categorical_crossentropy\", optimizer=Adam(learning_rate=0.00001), metrics=[\"acc\"])\n",
        "history = model.fit(train_x, train_y, epochs=100, verbose=1, validation_split=0.1, batch_size=16,\n",
        "                    callbacks=[plot_losses])"
      ],
      "metadata": {
        "id": "cYqxkVlPuAQf",
        "outputId": "c4c5d87e-7347-44ab-d091-acc825933593",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        }
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loss =  0.6327046751976013 , val_loss =  1.1872717142105103\n",
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r135/135 [==============================] - 4s 32ms/step - loss: 0.6327 - acc: 0.9477 - val_loss: 1.1873 - val_acc: 0.7542\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "history = model.fit(train_x, train_y, epochs=100, verbose=1, validation_split=0.1, batch_size=16,\n",
        "                    callbacks=[plot_losses])"
      ],
      "metadata": {
        "id": "nxjUi8r7xede",
        "outputId": "f9e6fb4c-3e0a-41fe-bc9a-e007ae7fe1b9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        }
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loss =  0.5531554818153381 , val_loss =  1.132599949836731\n",
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r135/135 [==============================] - 4s 31ms/step - loss: 0.5532 - acc: 0.9523 - val_loss: 1.1326 - val_acc: 0.7625\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "loss, acc = model.evaluate(test_x, test_y)\n",
        "print(\"loss=\", loss)\n",
        "print(\"acc=\", acc)\n",
        "\n",
        "\n",
        "y_ = model.predict(test_x)\n",
        "predicted = np.argmax(y_, axis=-1)\n",
        "plt.plot(test_y[:30], 'o')\n",
        "plt.plot(predicted[:30], '.')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "id": "wezUm_UwPiAn",
        "outputId": "d73771f2-c069-43f3-c419-0406d7de7ea0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "19/19 [==============================] - 1s 21ms/step - loss: 2.8153 - acc: 0.4183\n",
            "loss= 2.815264940261841\n",
            "acc= 0.4183333218097687\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "_jkambcyQcy1"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}