speech_command_identification.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "speech command identification.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true,
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
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              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "ok": true,
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "BD8If1VQ3qWD",
        "outputId": "8e612835-c0df-436e-e9f8-5c518a76d508"
      },
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-d384c029-89f0-48ae-b1a6-11e57fbb38fe\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-d384c029-89f0-48ae-b1a6-11e57fbb38fe\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "ename": "TypeError",
          "evalue": "ignored",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-21dc3c638f66>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mgoogle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolab\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0muploaded\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/google/colab/files.py\u001b[0m in \u001b[0;36mupload\u001b[0;34m()\u001b[0m\n\u001b[1;32m     67\u001b[0m   \u001b[0mlocal_filenames\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     68\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 69\u001b[0;31m   \u001b[0;32mwhile\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'action'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'complete'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     70\u001b[0m     result = _output.eval_js(\n\u001b[1;32m     71\u001b[0m         'google.colab._files._uploadFilesContinue(\"{output_id}\")'.format(\n",
            "\u001b[0;31mTypeError\u001b[0m: 'NoneType' object is not subscriptable"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-1Vc3zKGKbWg",
        "outputId": "d30b5429-1b1c-45db-9be0-f44f1d9b6a83"
      },
      "source": [
        "import os\n",
        "for dirname, _, filenames in os.walk('/content'):\n",
        "    for filename in filenames:\n",
        "        print(os.path.join(dirname, filename))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content/Data.zip\n",
            "/content/.config/.last_update_check.json\n",
            "/content/.config/gce\n",
            "/content/.config/config_sentinel\n",
            "/content/.config/.last_opt_in_prompt.yaml\n",
            "/content/.config/active_config\n",
            "/content/.config/.last_survey_prompt.yaml\n",
            "/content/.config/configurations/config_default\n",
            "/content/.config/logs/2021.09.30/17.11.05.914326.log\n",
            "/content/.config/logs/2021.09.30/17.12.14.546622.log\n",
            "/content/.config/logs/2021.09.30/17.11.26.623467.log\n",
            "/content/.config/logs/2021.09.30/17.11.46.319857.log\n",
            "/content/.config/logs/2021.09.30/17.11.53.276185.log\n",
            "/content/.config/logs/2021.09.30/17.12.13.730328.log\n",
            "/content/sample_data/README.md\n",
            "/content/sample_data/anscombe.json\n",
            "/content/sample_data/california_housing_train.csv\n",
            "/content/sample_data/california_housing_test.csv\n",
            "/content/sample_data/mnist_test.csv\n",
            "/content/sample_data/mnist_train_small.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rq4ad094KfPd"
      },
      "source": [
        "from os.path import isdir, join\n",
        "from pathlib import Path\n",
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4gBosn5NKicy"
      },
      "source": [
        "import numpy as np\n",
        "from scipy.fftpack import fft\n",
        "from scipy import signal\n",
        "from scipy.io import wavfile\n",
        "import librosa\n",
        "\n",
        "from sklearn.decomposition import PCA"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "WtHoDfQBKl4Z",
        "outputId": "e7ed3083-d032-4b4f-dc49-90e7a7f93e48"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import IPython.display as ipd\n",
        "import librosa.display\n",
        "\n",
        "import plotly.offline as py\n",
        "py.init_notebook_mode(connected=True)\n",
        "import plotly.graph_objs as go\n",
        "import plotly.tools as tls\n",
        "import pandas as pd\n",
        "\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/html": [
              "        <script type=\"text/javascript\">\n",
              "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
              "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
              "        if (typeof require !== 'undefined') {\n",
              "        require.undef(\"plotly\");\n",
              "        requirejs.config({\n",
              "            paths: {\n",
              "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
              "            }\n",
              "        });\n",
              "        require(['plotly'], function(Plotly) {\n",
              "            window._Plotly = Plotly;\n",
              "        });\n",
              "        }\n",
              "        </script>\n",
              "        "
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6UnAvTOQKo0P"
      },
      "source": [
        "import os\n",
        "import librosa   #for audio processing\n",
        "import IPython.display as ipd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from scipy.io import wavfile #for audio processing\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pQTX2OnGKrYu",
        "outputId": "96c6e6af-ef3d-46ac-c0c1-34ef76d16cc5"
      },
      "source": [
        "!unzip /content/Data.zip"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Archive:  /content/Data.zip\n",
            "   creating: places/Bampalapittiya/\n",
            "  inflating: places/Bampalapittiya/1.wav  \n",
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            "   creating: places/Batticaloa/\n",
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            "   creating: places/Colombo/\n",
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            "   creating: places/Dehiwala/\n",
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            "   creating: places/FacultyofMedicineColombouniversity/\n",
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            "   creating: places/Gampaha/\n",
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            "   creating: places/Jaffna/\n",
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            "   creating: places/Kalubowila/\n",
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            "   creating: places/Kandy/\n",
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            "   creating: places/SriLankaInstituteofInformationTechnology/\n",
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            "   creating: places/Trincomale/\n",
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            "   creating: places/UniversityofMoratuwa/\n",
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            "   creating: places/Wattala/\n",
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            "   creating: places/Wellawate/\n",
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            "  inflating: places/Wellawate/1.wav  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310
        },
        "id": "gbVgB81cKyif",
        "outputId": "e40aa7c0-9978-42cb-c078-b866e0397e2d"
      },
      "source": [
        "train_audio_path = '/content/places/'\n",
        "filename = 'Bampalapittiya/1.wav'\n",
        "sample_rate, samples = wavfile.read(str(train_audio_path) + filename)\n",
        "fig = plt.figure(figsize=(14, 8))\n",
        "ax1 = fig.add_subplot(211)\n",
        "ax1.set_title('Raw wave of ' + '/content/places/Bampalapittiya/1.wav')\n",
        "ax1.set_xlabel('time')\n",
        "ax1.set_ylabel('Amplitude')\n",
        "ax1.plot(np.arange(0, len(samples)/sample_rate, 1/sample_rate), samples)\n",
        "#librosa.display.waveplot(samples, sr=sample_rate, ax=ax1)\n",
        "print(sample_rate)\n",
        "print(len(samples))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "48000\n",
            "94240\n"
          ]
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7NI3KrCuK1qr"
      },
      "source": [
        "from IPython.display import Audio"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w1wPRJG6K6_q",
        "outputId": "d3c3b89e-bc6d-4c47-a1bd-1619ce6783a2"
      },
      "source": [
        "train_audio_path = '/content/places/'\n",
        "filename = 'Bampalapittiya/1.wav'\n",
        "sample_rate, samples = wavfile.read(str(train_audio_path) + filename)\n",
        "#ipd.Audio(samples, rate=sample_rate,autoplay=True)\n",
        "ipd.Audio('/content/places/Bampalapittiya/1.wav',autoplay=True)\n",
        "print(sample_rate)\n",
        "np.array(samples, dtype='float64')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "48000\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "array([[0., 0.],\n",
              "       [0., 0.],\n",
              "       [0., 0.],\n",
              "       ...,\n",
              "       [0., 0.],\n",
              "       [0., 0.],\n",
              "       [0., 0.]])"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kLWa6_b9LCM_"
      },
      "source": [
        "import scipy.signal as sps"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "AfLd6ttCLG5P",
        "outputId": "8bec4b17-d282-4220-dbb5-e073df6c22b5"
      },
      "source": [
        "samples=np.array(samples, dtype=\"float32\")\n",
        "\n",
        "sample_rate, samples=librosa.load('/content/places/Bampalapittiya/1.wav',sr=8000)\n",
        "ipd.Audio('/content/places/Bampalapittiya/1.wav',autoplay=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" autoplay=\"autoplay\">\n",
              "                    <source 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type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ],
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "uLQazIDPLI0y",
        "outputId": "1ee2a4fe-19c4-4422-b9d8-9aa94b6a7fcb"
      },
      "source": [
        "labels=os.listdir(train_audio_path)\n",
        " \n",
        "#find count of each label and plot bar graph\n",
        "no_of_recordings=[]\n",
        "for label in labels:\n",
        "    waves = [f for f in os.listdir(train_audio_path + label) if f.endswith('.wav')]\n",
        "    no_of_recordings.append(len(waves))\n",
        " \n",
        "plt.figure(figsize=(30,5))\n",
        "index = np.arange(len(labels))\n",
        "plt.bar(index, no_of_recordings)\n",
        "plt.xlabel('Commands', fontsize=12)\n",
        "plt.ylabel('No of recordings', fontsize=12)\n",
        "plt.xticks(index, labels, fontsize=15, rotation=60)\n",
        "plt.title('No. of recordings for each command')\n",
        "plt.show()\n",
        " \n",
        "labels=[\"Bampalapittiya\", \"Batticaloa\", \"Colombo\", \"Dehiwala\", \"FacultyofMedicineColombouniversity\", \"Gampaha\", \"Jaffna\", \"Kalubowila\", \"Kandy\", \"Kelany\",\"Kiribathgoda\",\"Kollupity\",\"Koswatta\",\"LibertyPlaza\",\"MagesticCity\",\"Malabe\",\"MarineDrive\",\"Marudhana\",\"Mattakuliya\",\"OneGalleFace\",\"Pettah\",\"Rajagiriya\",\"SriLankaInstituteofInformationTechnology\",\"Thalahena\",\"Trincomale\",\"UniversityofMoratuwa\",\"SriLankaInstituteofInformationTechnology\",\"Vavuniya\",\"Wattala\",\"Wellawate\"]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 2160x360 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8APPBcQ4LXHz"
      },
      "source": [
        "labels=[\"Bampalapittiya\", \"Batticaloa\", \"Colombo\", \"Dehiwala\", \"FacultyofMedicineColombouniversity\", \"Gampaha\", \"Jaffna\", \"Kalubowila\", \"Kandy\", \"Kelany\",\"Kiribathgoda\",\"Kollupity\",\"Koswatta\",\"LibertyPlaza\",\"MagesticCity\",\"Malabe\",\"MarineDrive\",\"Marudhana\",\"Mattakuliya\",\"OneGalleFace\",\"Pettah\",\"Rajagiriya\",\"SriLankaInstituteofInformationTechnology\",\"Thalahena\",\"Trincomale\",\"UniversityofMoratuwa\",\"SriLankaInstituteofInformationTechnology\",\"Vavuniya\",\"Wattala\",\"Wellawate\"]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cPdVgc6MLaet",
        "outputId": "b6ef72bd-a250-4628-e707-f36df83214a4"
      },
      "source": [
        "train_audio_path = '/content/places/'\n",
        "\n",
        "all_wave = []\n",
        "all_label = []\n",
        "for label in labels:\n",
        "    #print(label)\n",
        "    waves = [f for f in os.listdir(train_audio_path + '/'+ label) if f.endswith('.wav')]\n",
        "    for wav in waves:\n",
        "        samples, sample_rate = librosa.load(train_audio_path + '/' + label + '/' + wav, sr = 16000)\n",
        "        \n",
        "        samples = sps.resample(samples, 8000)\n",
        "        #print(len(samples))\n",
        "        if(len(samples)==8000) : \n",
        "            all_wave.append(samples)\n",
        "            all_label.append(label)  \n",
        "\n",
        "print(all_wave)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.00018224, -0.00017848,  0.00017488, ..., -0.00019456,\n",
            "        0.00019021, -0.00018619], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.02250055,  0.05326344,  0.0620673 , ..., -0.00127935,\n",
            "        0.00183087, -0.00329011], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
            "        0.00014079, -0.00013982], dtype=float32), array([ 0.00013876, -0.0001378 ,  0.00013681, ..., -0.00014185,\n",
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            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 4.6626694e-05, -4.7401521e-05,  4.8090897e-05, ...,\n",
            "       -4.4104687e-05,  4.5046640e-05, -4.5882243e-05], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([ 0.00022083, -0.0001824 ,  0.000151  , ..., -0.00026361,\n",
            "        0.00032449, -0.00026836], dtype=float32), array([-3.0336238e-05,  3.8186114e-05, -3.9188060e-05, ...,\n",
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            "        5.1130515e-05,  1.2524315e-07,  7.7608020e-05], dtype=float32), array([-3.0336238e-05,  3.8186114e-05, -3.9188060e-05, ...,\n",
            "        5.1130515e-05,  1.2524315e-07,  7.7608020e-05], dtype=float32), array([-3.0336238e-05,  3.8186114e-05, -3.9188060e-05, ...,\n",
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            "        5.1130515e-05,  1.2524315e-07,  7.7608020e-05], dtype=float32), array([-3.0336238e-05,  3.8186114e-05, -3.9188060e-05, ...,\n",
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            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
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            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-5.2460698e-05,  4.7313239e-05, -4.6411980e-05, ...,\n",
            "       -1.5083268e-04, -2.0228223e-04, -9.5394214e-05], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
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            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
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            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([-0.00025686,  0.00025709, -0.00025718, ...,  0.00025619,\n",
            "       -0.00025646,  0.00025673], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00015986, -0.00016008,  0.00016036, ..., -0.00015909,\n",
            "        0.00015936, -0.00015963], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 0.00019063, -0.00017225,  0.00015895, ...,  0.00091523,\n",
            "        0.00031858, -0.00075765], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 8.9425761e-05, -8.7278531e-05,  8.5298125e-05, ...,\n",
            "       -9.6224925e-05,  9.3804825e-05, -9.1553935e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([ 1.6756096e-05, -1.8330658e-05,  1.8638459e-05, ...,\n",
            "       -5.5927947e-05, -1.2319973e-05, -3.6948575e-05], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
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            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([-0.00016045,  0.00015965, -0.00015892, ...,  0.00016291,\n",
            "       -0.00016209,  0.00016124], dtype=float32), array([ 0.0004045 , -0.00040669,  0.00038488, ..., -0.00029556,\n",
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            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([ 0.00017518, -0.00017356,  0.000172  , ..., -0.00018047,\n",
            "        0.00017865, -0.00017684], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([-6.0719372e-05,  2.3140815e-06,  9.4091656e-06, ...,\n",
            "       -8.1498103e-05, -1.4014845e-04, -2.3807249e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 9.8243931e-05, -2.4135948e-05, -2.2873137e-06, ...,\n",
            "       -2.5345694e-04, -3.0036038e-04,  1.3042601e-04], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 5.9394330e-05, -5.9190381e-05,  5.9028152e-05, ...,\n",
            "       -6.0015434e-05,  5.9811486e-05, -5.9602906e-05], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([ 0.00041147, -0.0004064 ,  0.00040146, ..., -0.0004279 ,\n",
            "        0.00042221, -0.00041673], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([-9.7394977e-06,  8.9330424e-06, -8.1521312e-06, ...,\n",
            "        1.2563004e-05, -1.1555391e-05,  1.0654515e-05], dtype=float32), array([ 4.7779900e-05, -4.8026130e-05,  4.8284081e-05, ...,\n",
            "       -4.6935693e-05,  4.7211233e-05, -4.7428144e-05], dtype=float32), array([ 4.7779900e-05, -4.8026130e-05,  4.8284081e-05, ...,\n",
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            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 0.00050086, -0.00041811,  0.00039401, ...,  0.00061282,\n",
            "        0.00172532,  0.00059306], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([ 2.3116670e-05, -2.9247671e-05,  3.0015910e-05, ...,\n",
            "       -4.2631396e-05, -3.3610402e-06, -7.0508373e-05], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32), array([-0.10738499, -0.18149535, -0.13413158, ...,  0.00128388,\n",
            "       -0.01190551,  0.01052771], dtype=float32)]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ba2TpK6OyWk"
      },
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "le = LabelEncoder()\n",
        "y=le.fit_transform(all_label)\n",
        "classes= list(le.classes_)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2Og9D2OlO1kT",
        "outputId": "ad0ecbe5-467e-42a1-cd15-7280bb13e0f5"
      },
      "source": [
        "from keras.utils import np_utils\n",
        "y=np_utils.to_categorical(y, num_classes=len(labels))\n",
        "print(y.shape)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(600, 30)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "63uEVGm1O5UB",
        "outputId": "1d38d778-c050-4261-becd-c51f242b060a"
      },
      "source": [
        "print(np.array(all_wave).ndim)\n",
        "#all_wave=np.reshape(np.array(all_wave),(-1,2))\n",
        "print(np.array(all_wave).shape)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "2\n",
            "(600, 8000)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9WSj9AZrO8QV",
        "outputId": "e38e9259-7f64-4694-ebcc-1a6152a3595e"
      },
      "source": [
        "a=np.array(np.array(all_wave).reshape(-1,8000,1))\n",
        "\n",
        "print(a.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(600, 8000, 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kehfsiEpPGu6"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "x_tr, x_val, y_tr, y_val = train_test_split(np.array(all_wave),np.array(y),stratify=y,test_size = 0.2,random_state=777,shuffle=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r3k0HfuCPKVH",
        "outputId": "5a85421b-d597-462e-d114-f9d1cbb50d8f"
      },
      "source": [
        "from keras.layers import Dense, Dropout, Flatten, Conv1D, Input, MaxPooling1D\n",
        "from keras.models import Model\n",
        "from keras.callbacks import EarlyStopping, ModelCheckpoint\n",
        "from keras import backend as K\n",
        "K.clear_session()\n",
        "\n",
        "inputs = Input(shape=(8000,1))\n",
        "\n",
        "#First Conv1D layer\n",
        "conv = Conv1D(8,13, padding='valid', activation='relu', strides=1)(inputs)\n",
        "conv = MaxPooling1D(3)(conv)\n",
        "conv = Dropout(0.3)(conv)\n",
        "\n",
        "#Second Conv1D layer\n",
        "conv = Conv1D(16, 11, padding='valid', activation='relu', strides=1)(conv)\n",
        "conv = MaxPooling1D(3)(conv)\n",
        "conv = Dropout(0.3)(conv)\n",
        "\n",
        "#Third Conv1D layer\n",
        "conv = Conv1D(32, 9, padding='valid', activation='relu', strides=1)(conv)\n",
        "conv = MaxPooling1D(3)(conv)\n",
        "conv = Dropout(0.3)(conv)\n",
        "\n",
        "#Fourth Conv1D layer\n",
        "conv = Conv1D(64, 7, padding='valid', activation='relu', strides=1)(conv)\n",
        "conv = MaxPooling1D(3)(conv)\n",
        "conv = Dropout(0.3)(conv)\n",
        "\n",
        "#Flatten layer\n",
        "conv = Flatten()(conv)\n",
        "\n",
        "#Dense Layer 1\n",
        "conv = Dense(256, activation='relu')(conv)\n",
        "conv = Dropout(0.3)(conv)\n",
        "\n",
        "#Dense Layer 2\n",
        "conv = Dense(128, activation='relu')(conv)\n",
        "conv = Dropout(0.3)(conv)\n",
        "\n",
        "outputs = Dense(len(labels), activation='softmax')(conv)\n",
        "\n",
        "model = Model(inputs, outputs)\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_1 (InputLayer)         [(None, 8000, 1)]         0         \n",
            "_________________________________________________________________\n",
            "conv1d (Conv1D)              (None, 7988, 8)           112       \n",
            "_________________________________________________________________\n",
            "max_pooling1d (MaxPooling1D) (None, 2662, 8)           0         \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 2662, 8)           0         \n",
            "_________________________________________________________________\n",
            "conv1d_1 (Conv1D)            (None, 2652, 16)          1424      \n",
            "_________________________________________________________________\n",
            "max_pooling1d_1 (MaxPooling1 (None, 884, 16)           0         \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 884, 16)           0         \n",
            "_________________________________________________________________\n",
            "conv1d_2 (Conv1D)            (None, 876, 32)           4640      \n",
            "_________________________________________________________________\n",
            "max_pooling1d_2 (MaxPooling1 (None, 292, 32)           0         \n",
            "_________________________________________________________________\n",
            "dropout_2 (Dropout)          (None, 292, 32)           0         \n",
            "_________________________________________________________________\n",
            "conv1d_3 (Conv1D)            (None, 286, 64)           14400     \n",
            "_________________________________________________________________\n",
            "max_pooling1d_3 (MaxPooling1 (None, 95, 64)            0         \n",
            "_________________________________________________________________\n",
            "dropout_3 (Dropout)          (None, 95, 64)            0         \n",
            "_________________________________________________________________\n",
            "flatten (Flatten)            (None, 6080)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 256)               1556736   \n",
            "_________________________________________________________________\n",
            "dropout_4 (Dropout)          (None, 256)               0         \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 128)               32896     \n",
            "_________________________________________________________________\n",
            "dropout_5 (Dropout)          (None, 128)               0         \n",
            "_________________________________________________________________\n",
            "dense_2 (Dense)              (None, 30)                3870      \n",
            "=================================================================\n",
            "Total params: 1,614,078\n",
            "Trainable params: 1,614,078\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Av3bSz-XPSMa"
      },
      "source": [
        "model.compile(loss='categorical_crossentropy',optimizer='sgd',metrics=['accuracy'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1fjX-WNMPWHc"
      },
      "source": [
        "es = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=10, min_delta=0.00001) \n",
        "mc = ModelCheckpoint('best_model.hdf5', monitor='val_acc', verbose=1, save_best_only=True, mode='max')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i5SliXmVPYdf",
        "outputId": "7b8b8a66-1a80-4c36-daa6-f0a5f3ed77f6"
      },
      "source": [
        "history=model.fit(x_tr, y_tr ,epochs=100, callbacks=[es,mc], batch_size=32, validation_data=(x_val,y_val))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/100\n",
            "15/15 [==============================] - 5s 256ms/step - loss: 3.4039 - accuracy: 0.0354 - val_loss: 3.3962 - val_accuracy: 0.0667\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 2/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 3.3936 - accuracy: 0.0417 - val_loss: 3.3917 - val_accuracy: 0.0667\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 3/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 3.3907 - accuracy: 0.0396 - val_loss: 3.3879 - val_accuracy: 0.1333\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 4/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 3.3824 - accuracy: 0.0437 - val_loss: 3.3838 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 5/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 3.3799 - accuracy: 0.0604 - val_loss: 3.3794 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 6/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 3.3683 - accuracy: 0.0792 - val_loss: 3.3739 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 7/100\n",
            "15/15 [==============================] - 4s 241ms/step - loss: 3.3610 - accuracy: 0.0854 - val_loss: 3.3673 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 8/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 3.3518 - accuracy: 0.0792 - val_loss: 3.3586 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 9/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 3.3318 - accuracy: 0.1167 - val_loss: 3.3469 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 10/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 3.3151 - accuracy: 0.0917 - val_loss: 3.3312 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 11/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 3.2888 - accuracy: 0.1229 - val_loss: 3.3093 - val_accuracy: 0.1000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 12/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 3.2558 - accuracy: 0.1208 - val_loss: 3.2742 - val_accuracy: 0.1667\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 13/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 3.1962 - accuracy: 0.1583 - val_loss: 3.2180 - val_accuracy: 0.1667\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 14/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 3.1070 - accuracy: 0.1771 - val_loss: 3.1209 - val_accuracy: 0.2667\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 15/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 2.9841 - accuracy: 0.1833 - val_loss: 2.9583 - val_accuracy: 0.5333\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 16/100\n",
            "15/15 [==============================] - 4s 241ms/step - loss: 2.8075 - accuracy: 0.2542 - val_loss: 2.6686 - val_accuracy: 0.7000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 17/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 2.4475 - accuracy: 0.3313 - val_loss: 2.2065 - val_accuracy: 0.8333\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 18/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 1.9701 - accuracy: 0.4521 - val_loss: 1.5508 - val_accuracy: 0.8333\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 19/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 1.4937 - accuracy: 0.5854 - val_loss: 0.9687 - val_accuracy: 0.9667\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 20/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 1.0774 - accuracy: 0.6521 - val_loss: 0.4902 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 21/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.7243 - accuracy: 0.8062 - val_loss: 0.2702 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 22/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.5741 - accuracy: 0.8313 - val_loss: 0.1603 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 23/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.4135 - accuracy: 0.8833 - val_loss: 0.0745 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 24/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.2997 - accuracy: 0.9146 - val_loss: 0.0489 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 25/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.2400 - accuracy: 0.9438 - val_loss: 0.0267 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 26/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.2221 - accuracy: 0.9396 - val_loss: 0.0232 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 27/100\n",
            "15/15 [==============================] - 4s 236ms/step - loss: 0.2055 - accuracy: 0.9354 - val_loss: 0.0127 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 28/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.1434 - accuracy: 0.9625 - val_loss: 0.0088 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 29/100\n",
            "15/15 [==============================] - 4s 235ms/step - loss: 0.1549 - accuracy: 0.9646 - val_loss: 0.0071 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 30/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.1295 - accuracy: 0.9688 - val_loss: 0.0053 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 31/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.1298 - accuracy: 0.9604 - val_loss: 0.0041 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 32/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0683 - accuracy: 0.9833 - val_loss: 0.0020 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 33/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0982 - accuracy: 0.9708 - val_loss: 0.0018 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 34/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.1195 - accuracy: 0.9667 - val_loss: 0.0026 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 35/100\n",
            "15/15 [==============================] - 4s 235ms/step - loss: 0.1054 - accuracy: 0.9667 - val_loss: 0.0021 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 36/100\n",
            "15/15 [==============================] - 4s 235ms/step - loss: 0.0631 - accuracy: 0.9854 - val_loss: 0.0014 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 37/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0827 - accuracy: 0.9750 - val_loss: 0.0014 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 38/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0654 - accuracy: 0.9812 - val_loss: 0.0013 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 39/100\n",
            "15/15 [==============================] - 4s 241ms/step - loss: 0.0482 - accuracy: 0.9896 - val_loss: 0.0012 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 40/100\n",
            "15/15 [==============================] - 4s 241ms/step - loss: 0.0743 - accuracy: 0.9812 - val_loss: 0.0022 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 41/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0653 - accuracy: 0.9812 - val_loss: 0.0013 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 42/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0588 - accuracy: 0.9812 - val_loss: 9.3192e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 43/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0660 - accuracy: 0.9771 - val_loss: 0.0010 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 44/100\n",
            "15/15 [==============================] - 4s 235ms/step - loss: 0.0390 - accuracy: 0.9896 - val_loss: 6.0671e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 45/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0247 - accuracy: 0.9958 - val_loss: 4.6926e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 46/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0244 - accuracy: 0.9917 - val_loss: 4.0692e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 47/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0228 - accuracy: 0.9958 - val_loss: 3.1429e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 48/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0266 - accuracy: 0.9937 - val_loss: 2.7760e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 49/100\n",
            "15/15 [==============================] - 4s 241ms/step - loss: 0.0227 - accuracy: 0.9979 - val_loss: 2.1746e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 50/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0430 - accuracy: 0.9875 - val_loss: 2.0456e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 51/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0202 - accuracy: 0.9958 - val_loss: 1.9575e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 52/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0210 - accuracy: 0.9937 - val_loss: 1.7204e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 53/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0644 - accuracy: 0.9896 - val_loss: 1.8014e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 54/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0180 - accuracy: 0.9979 - val_loss: 1.5071e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 55/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0165 - accuracy: 0.9937 - val_loss: 1.4136e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 56/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0274 - accuracy: 0.9917 - val_loss: 1.1876e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 57/100\n",
            "15/15 [==============================] - 4s 236ms/step - loss: 0.0283 - accuracy: 0.9917 - val_loss: 1.6204e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 58/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0322 - accuracy: 0.9896 - val_loss: 1.3804e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 59/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0260 - accuracy: 0.9896 - val_loss: 1.1388e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 60/100\n",
            "15/15 [==============================] - 4s 236ms/step - loss: 0.0245 - accuracy: 0.9937 - val_loss: 1.3317e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 61/100\n",
            "15/15 [==============================] - 4s 236ms/step - loss: 0.0189 - accuracy: 0.9937 - val_loss: 9.4696e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 62/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0436 - accuracy: 0.9896 - val_loss: 1.1377e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 63/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0163 - accuracy: 0.9958 - val_loss: 8.3190e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 64/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 6.7251e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 65/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0334 - accuracy: 0.9958 - val_loss: 7.8568e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 66/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0262 - accuracy: 0.9896 - val_loss: 9.6210e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 67/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0257 - accuracy: 0.9937 - val_loss: 1.0847e-04 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 68/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0169 - accuracy: 0.9958 - val_loss: 7.5318e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 69/100\n",
            "15/15 [==============================] - 4s 236ms/step - loss: 0.0329 - accuracy: 0.9896 - val_loss: 9.0859e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 70/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0169 - accuracy: 0.9979 - val_loss: 5.6408e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 71/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0096 - accuracy: 0.9979 - val_loss: 4.7696e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 72/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0233 - accuracy: 0.9958 - val_loss: 5.3857e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 73/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0152 - accuracy: 0.9958 - val_loss: 5.0127e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 74/100\n",
            "15/15 [==============================] - 4s 241ms/step - loss: 0.0253 - accuracy: 0.9917 - val_loss: 6.1056e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 75/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0130 - accuracy: 0.9958 - val_loss: 4.9189e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 76/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0183 - accuracy: 0.9937 - val_loss: 5.1284e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 77/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0114 - accuracy: 0.9979 - val_loss: 3.7513e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 78/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0181 - accuracy: 0.9958 - val_loss: 3.6861e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 79/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0216 - accuracy: 0.9958 - val_loss: 6.3326e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 80/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0332 - accuracy: 0.9896 - val_loss: 5.7750e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 81/100\n",
            "15/15 [==============================] - 4s 237ms/step - loss: 0.0147 - accuracy: 0.9958 - val_loss: 5.0484e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 82/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0125 - accuracy: 0.9958 - val_loss: 3.6857e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 83/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0206 - accuracy: 0.9937 - val_loss: 3.0723e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 84/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0156 - accuracy: 0.9979 - val_loss: 2.1576e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 85/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0202 - accuracy: 0.9917 - val_loss: 2.9523e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 86/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0089 - accuracy: 0.9979 - val_loss: 3.1621e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 87/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0170 - accuracy: 0.9958 - val_loss: 2.7242e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 88/100\n",
            "15/15 [==============================] - 4s 238ms/step - loss: 0.0073 - accuracy: 0.9979 - val_loss: 2.5140e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 89/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0094 - accuracy: 0.9979 - val_loss: 1.9319e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 90/100\n",
            "15/15 [==============================] - 4s 236ms/step - loss: 0.0102 - accuracy: 0.9958 - val_loss: 2.2136e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 91/100\n",
            "15/15 [==============================] - 4s 239ms/step - loss: 0.0124 - accuracy: 0.9958 - val_loss: 1.7579e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 92/100\n",
            "15/15 [==============================] - 4s 241ms/step - loss: 0.0258 - accuracy: 0.9917 - val_loss: 1.8453e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 93/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0200 - accuracy: 0.9917 - val_loss: 1.7770e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 94/100\n",
            "15/15 [==============================] - 4s 240ms/step - loss: 0.0111 - accuracy: 0.9979 - val_loss: 1.5942e-05 - val_accuracy: 1.0000\n",
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n",
            "Epoch 00094: early stopping\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z-x7-baIQrsi"
      },
      "source": [
        "model.save('best_model.hdf5')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "eONDby7-Q7Ff",
        "outputId": "648645b4-7795-4b96-8ff5-c8f5f10c9f3c"
      },
      "source": [
        "from matplotlib import pyplot \n",
        "pyplot.plot(history.history['loss'], label='train') \n",
        "pyplot.plot(history.history['val_accuracy'], label='test') \n",
        "pyplot.legend() \n",
        "pyplot.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "image/png": 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8+OKL5OfnR/7Fezqhu3VSPVz21LXzmzeP838vXxyRecBFZOqbujX009SkY8E5xxe/+EU+9rGPnbJux44dbNy4kb/5m7/hmmuu4f7774/si0egy+IDzx0gNyOFj1x+RoQKJSJTnWroQwydPve6667j0UcfpbMzcDOF2tpaTpw4QV1dHVlZWdx5553cc8897Nix45R9J80T7LI4wUFFb9Z4eHZPAx+5/IzBkaAikvimbg09DoZOn7tu3Tpuv/12LrnkEgBycnL46U9/yqFDh7jnnntISkoiNTWVhx9+GIANGzawdu1aSkpKJn9RdCDQJ1hD/8az+ynISuX/Xl4+uXKIyLSiQB/hscceG/b87rvvHvZ8yZIlXHfddafs9+lPf5pPf/rTkSlEWzUkpUDuvLB33VHVyqb9jXxh7TJyw7iZsohMf2pymYo81ZBXAknhz2b4ZGU12WnJfPCS8siXS0SmNAX6VOSpgfzwJ8ny+x3P7T3BVcvmkD2BmwWLyPQ25QI9XndQiqVx32Nb9YQGFb1R00ZjRw/vXqE7CInMRFMq0DMyMmhubk7oUHfO0dzcTEZGxugb+Pqho25CPVye3dNAcpJx9TIFushMNKW+l5eWllJTU0NjY2O8ixJVGRkZlJaOUQPvqAPnn1APl+f2NnBh+SwKsjSQSGQmmlKBnpqayuLFi+NdjPia4LS5x5pPcqChky/fuCIKhRKR6WBKNbkIb48SLQjvouizexoAuHb53EiXSESmCQX6VDNw67kwa+jP7mlg2dxcFhZqVkWRmUqBPtW0VUNWEaRmhrxL68leKo+1qneLyAw3pdrQZ6y3/gidJwI/170Wdg+XTftP4PM7rl0R/shSEUkcCvR466iHH68fvmzVHWEd4uk36piTm865C6Iwla+ITBsK9HhrPRp4XP8dWBiYCIxZi0Le/dk9Dbywv5F7rltGUtLkblcnItObAj3eBroplq2BovDuLNTh7ePL/7uLs+fl8tErNO+5yEynQI+3CfZqAfjn3+2nocPLw3eeT1qKrm+LzHQhpYCZrTWz/WZ2yMzuG2X9QjPbZGavmdlOM7s+8kVNUG3VkDkb0rLD2m37sRZ++uox7rq0nNULZ0WpcCIynYwb6GaWDDwIrANWALeZ2cjhiH8DPOGcWw3cCjwU6YImLE9N2L1anHP89c93UZKfyeffsyxKBROR6SaUGvoa4JBz7i3nXC/wOHDTiG0ckBf8OR+oi1wRE5ynOux5W9q7+9nf0MFfXrJI0+SKyKBQAn0BUD3keU1w2VB/B9xpZjXARmDUW/eY2QYzqzSzykSfgCskzgWnyg0v0OvbvQCUFIQ++EhEEl+krqTdBvzQOVcKXA/8xMxOObZz7hHnXIVzrqK4uDhCLz2NdbdC38mwm1wagoE+N2+MKXhFZEYKJdBrgaGJUxpcNtSHgScAnHNbgAygKBIFTGieic2sOFBDn6dAF5EhQgn0bcBSM1tsZmkELno+PWKbKuAaADNbTiDQ1aYynsGpcsOroZ8IBvqcvPRIl0hEprFxA9051w98Cvg9sJdAb5bdZvZVMxsYs/454KNm9gbwM+Aul8i3HYqUCU6VW9/upSArlYzU8G8iLSKJK6QuEs65jQQudg5ddv+Qn/cAl0W2aDOApxpSMiGrMKzdGtp7mJur5hYRGU7DC+OprSrQfm7hzcHS0O5lbr4CXUSGU6DH0wQGFUEw0HPVfi4iwynQ42kCg4r6fX4aO3qYpxq6iIygQI+Xvm442Rh2oDef7MXvYI66LIrICAr0eBns4RLmKFGP+qCLyOgU6PHimVgf9LdHiaoNXUSGU6DHS9vERok2aJSoiIxBgR4vnmqwJMgrCWu3hvYekpOMwhzV0EVkOAV6vHhqILcEklPD2q2+3UtxTjrJun+oiIygQI+XtuoJ3Xauod2r9nMRGZUCPV48VRMfVKT2cxEZhQI9Hvw+aK8Lu4cLBOdxUaCLyCgU6PHQUQ/+/rCbXLx9PjzdfRolKiKjUqDHw0Af9DCnzR3osjhH87iIyCgU6PEwMEo03DsVDYwSVQ1dREahQI+HjuOBx9z5Ye3W0NED6F6iIjI6BXo8dDZASgZk5Ie1W4NHN4cWkbEp0OOhowFy5oR9Y4v6di8ZqUnkZYR0oykRmWEU6PHQ2QA588LeraHdy7y8DCzMPwQiMjMo0OOhM1hDD1NDu1fzoIvImBTo8dDZALkTqaH3aJZFERmTAj3W+nuguxVy5oa1m3OOes3jIiKnoUCPtc4TgccwA93T3Udvv189XERkTAr0WOtsCDyGGej17RpUJCKnp0CPtYFAzw0v0GtaugGYr0AXkTEo0GOtoz7wGGa3xe1VraQmGyvmhzcYSURmDgV6rHU2AAbZxWHttvVIC+csyCczLTk65RKRaU+BHmudDZBdBMmhj/b09vnYWdPGmsWzo1gwEZnuFOix1tEQ9gXR16vb6PM51pQr0EVkbAr0WOsMP9C3HmnBDCoWKdBFZGwK9FibQKBvO9rCsrm55GelRqlQIpIIFOix5PcHBhaF0WWx3+dn+7FWtZ+LyLhCCnQzW2tm+83skJndN8Y2N5vZHjPbbWaPRbaYCaK7Ffx9YdXQd9e109Xr40K1n4vIOMbtamFmycCDwLVADbDNzJ52zu0Zss1S4IvAZc65VjMLfyrBmWACo0S3HW0BUA1dRMYVSg19DXDIOfeWc64XeBy4acQ2HwUedM61AjjnTkS2mAmic2BQUeiBvvVIC4sKszSHi4iMK5RAXwBUD3leE1w21FnAWWb2spm9YmZrRzuQmW0ws0ozq2xsbJxYiaezgYm5Qpw61+93bDvaouYWEQlJpC6KpgBLgauA24DvmVnByI2cc4845yqccxXFxeGNlEwIg8P+Q2uROtzYSWtXn5pbRCQkoQR6LVA25HlpcNlQNcDTzrk+59wR4ACBgJehOk9Aajak54a0+daB9nPV0EUkBKEE+jZgqZktNrM04Fbg6RHb/C+B2jlmVkSgCeatCJYzMXTWh3Xrud117eRnprKoMCuKhRKRRDFuoDvn+oFPAb8H9gJPOOd2m9lXzWx9cLPfA81mtgfYBNzjnGuOVqGnrc4TYd16rq6tm7LZmboptIiEJKQZopxzG4GNI5bdP+RnB3w2+E/G0lEPc1eEvHltazdnFGdHsUAikkg0UjSWOk+EPA+6c47atm5KCjKjXCgRSRQK9Fjp64YeT8ht6J7uPrp6fSxQoItIiBTosTJ467nQaug1rYFbzpXOUqCLSGgU6LHSEd6w/9q2QKCryUVEQqVAj5Uw53GpCwa6mlxEJFQK9FgJM9BrW7vJSE1idnZaFAslIolEgR4rnQ1gSYH7iYZgoIeL+qCLSKgU6LHSUQ/ZxZCUHNLmdW3dam4RkbAo0GOluxWyCkPevLatWz1cRCQsCvRY8XogPS+0Tft8NHX2UpKvQBeR0CnQY6WnHTJCC/TBHi6qoYtIGBToseJth4z8kDatVZdFEZkABXqshNHkUtuqQUUiEj4Feiw4F3aTS5LBvHzdR1REQqdAj4W+bvD3h9zkUtPWzby8DFKT9d8jIqFTYsSC1xN4DKPJRc0tIhIuBXos9LQHHkOsodd5utXDRUTCpkCPBW/oge7zO463edXDRUTCpkCPhZ7Qm1xOdHjp9zs1uYhI2BTosTDQhh5CDV2DikRkohTosTDY5DJ+DX3wTkWqoYtImBTosTBwUTSEJhfdqUhEJkqBHgteD1gypGWPu2ltazcFWalkp6fEoGAikkgU6LHgDY4SDeFmFZoHXUQmSoEeCz3toQ8qatOgIhGZGAV6LHg9IfVwcc5R3dLNwtlZMSiUiCQaBXoshDh1blNnL919PgW6iEyIAj0WQmxyqWrpAlCgi8iEKNBjIcQml+pgoJfNVhu6iIRPgR4L3tDmQh+ooZfOUg1dRMKnQI82vz+sJpe5eelkpCbHoGAikmgU6NHW2wG4kJtc1H4uIhMVUqCb2Voz229mh8zsvtNs92dm5sysInJFnObCmMeluqWLMgW6iEzQuIFuZsnAg8A6YAVwm5mtGGW7XOBu4NVIF3JaC3Eel55+H8fbvZSp/VxEJiiUGvoa4JBz7i3nXC/wOHDTKNv9PfB1wBvB8k1/IU6dW9vajXPqsigiExdKoC8Aqoc8rwkuG2Rm5wNlzrnfnO5AZrbBzCrNrLKxsTHswk5LITa5DPZBL1Sgi8jETPqiqJklAd8APjfets65R5xzFc65iuLi4sm+9PQw2ORy+hp6dXAedNXQRWSiQgn0WqBsyPPS4LIBucA5wAtmdhS4GHhaF0aDQmxyqW7pIj0lieKc9BgUSkQSUSiBvg1YamaLzSwNuBV4emClc87jnCtyzpU758qBV4D1zrnKqJR4uhkM9HGaXJq7KJ2VSVLS+FPsioiMZtxAd871A58Cfg/sBZ5wzu02s6+a2fpoF3Da62mH5HRIOX3Nu0p90EVkkkK6LY5zbiOwccSy+8fY9qrJFyuBhDCPS2Da3C4uLJ8Vo0KJSCLSSNFoC2Eel7auPjp6+jWoSEQmRYEebSHM41LdqmlzRWTyFOjRFkKTS9XgtLkKdBGZOAV6tIXQ5KJAF5FIUKBHWyhNLi1dFGankZMe0jVqEZFRKdCjLcQmF9XORWSyFOjR5OuDvq4QRol264KoiEyaAj2aejoCj6dpcun3+alt69Z9REVk0hTo0RTCPC5Hm7vw+R3lhdkxKpSIJCoFejSFMI/Lzpo2AFaWjn+LOhGR01GgR1MIdyvaWeMhKy2ZpXNyY1QoEUlUCvRoGry5xdi17zdq2jinJJ9kzbIoIpOkQI+mcZpc+nx+9tS1c66aW0QkAhTo0TROk8v++g56+v2cW1YQw0KJSKJSoEeT9/SBvrMmUIM/TzV0EYkABXo0eT2QlgPJow/p31nTRkFWqgYViUhEKNCjqcdz2h4ub9R4WLkgHzNdEBWRyVOgR5O3fcweLt29Pg40dHBeqdrPRSQyFOjR5PWM2cNlz3EPPr9TDxcRiRgFejSdZurcN6qDF0TVw0VEIkSBHk2naXLZWdPG3Lx05uZlxLhQIpKoFOjR1NUMmaPXwHfWeDhX7eciEkEK9Gg52QzeNph9ximrPN19vNV0Uv3PRSSiFOjR0rQ/8Fi07JRVu2oD7eeqoYtIJCnQo6UxGOjFZ52y6rWqVgB1WRSRiFKgR0vTAUjNgrzSU1btqGpj6Zwc8rNS41AwEUlUCvRoadwPRUshafgp9vsdO6paOX/hrDgVTEQSlQI9WpoOjNp+/lbTSdq6+rhgkQJdRCJLgR4NPZ3gqYaiU9vPdwTbz89XoItIhCnQo6H5UOBxlAuiO461kp+ZyhlFuim0iESWAj0amg4EHkdpctl+rJXzFxaQpFvOiUiEKdCjoXE/WPIpg4o8XX0cPNGp9nMRiYqQAt3M1prZfjM7ZGb3jbL+s2a2x8x2mtkfzGxR5Is6jTTtD4R5Stqwxa9Vq/1cRKJn3EA3s2TgQWAdsAK4zcxWjNjsNaDCOXcu8BTwz5Eu6LTSeACKT21u2XGslSTTgCIRiY5QauhrgEPOubecc73A48BNQzdwzm1yznUFn74CnDqaZqbw9UHL4VF7uGyvamX5/Dyy00e/JZ2IyGSEEugLgOohz2uCy8byYeC3o60wsw1mVmlmlY2NjaGXcjppOQL+/lNq6D6/4/WqNrWfi0jURPSiqJndCVQA/zLaeufcI865CudcRXFxcSRfeuoYnJRreA19f30HJ3t9GiEqIlETynf/WqBsyPPS4LJhzOzdwJeAdzrneiJTvGloYFKuoqXDFm8PDihSDV1EoiWUQN8GLDWzxQSC/Fbg9qEbmNlq4D+Atc65ExEv5XTSdADyFkB6LgB7j7fz+NYqfv5aLfPzMyidlRnnAopIoho30J1z/Wb2KeD3QDLwqHNut5l9Fah0zj1NoIklB3jSzACqnHPro1juqatxPxSdRXevjw0/qeTFg02kpSSx7px5fOzKJQTPj4hIxIXU3cI5txHYOGLZ/UN+fneEyzU9OQdNB3Gr7+RzT77OS4eauHft2dx6YRmzstPG319EZBLUf26yanfA8/8Azgd+H/Sd5NnGAjburedL1y/no1eeegs6EZFo0Jv3/ogAAAmCSURBVND/ydrxIzj6EvR1g6+XhqKL+eq+Em6/aCEfuWJxvEsnIjOIauiTdWwLnPFOuONJDjd2ct0Df+KSMwv5yvp3qL1cRGJKNfTJONkU6He+8BIAfvjyUZKSjAduWUVqsk6tiMSWUmcyqrYEHhddSru3j//ZUcN7zy2hKCc9vuUSkRlJgT4Zx7ZASgaUrOapyhq6en3cdWl5vEslIjOUAn0yjr0MCyrwJ6Xx4y1HOX9hAStL8+NdKhGZoRIr0J+8C7Z+Lzav1dMB9Tth0SX88UAjR5u7+KBq5yISR4kT6B0NsPsXgT7hPR3Rf73qreD8sOhSfrj5KMW56aw7Z370X1dEZAyJE+hVmwOP3jbY9oOovtSjLx3h6V/9Dz6SefhwIX880MgdFy0kLSVxTqeITD+Jk0DHtkBqFpRfAVseDAz0mQRvn4/Ht1bR0+8btry2rZuv/XYfpe2vsZdyvv58DZmpydy+ZuGkXk9EZLISJ9CrNkPphfDOe+HkCXjtp5M63E9fOcZ9P3+T7zx/aNjy7zx/kFT6WJ10mHMuXssb97+Hl+69mjl5GZN6PRGRyUqMQO9ug/pdsOhSKL8cyi6Cl78VuB3cBPj8jh9vOYYZPPzCYfbVtwNQ1dzFk5U1fGZFJ+brgUWXkp+VSqH6nYvIFJAYgV69FXCBQDeDKz4PnmrY8WPoagn730s7D+BpOcHX1pZSluHlH57cjO9kC997Zjuzk05ya+HhwOsGR4iKiEwF5pyLywtXVFS4ysrKyBzs2b8NtJvfVwVpWYFpbP/jCqh/MzLHH03x2fDJV6N3fBGRUZjZdudcxWjrEmNyrqotULIqEOYQqKX/+Q/h0HNhH6qps4fvbDrE1cvm8M6zinE4/uvVKg6d6CQ1OYm7372UnLQUWHhxZN+DiMgkTf9A7+sOzEl+8ceHLy86M/BvHD6/w4CkpMDMiP/+y138jLP45PvfBbnpGHDVsi7+9d9f4q5Ly8m58qzTHk9EJF6mf6DXVIK/DxZdFtZuu+s8/Pe2an7xWi2Zqcl8oKKU61fO56ntNdx47nyKc9++0Fk6K4tXvngNGanJkS69iEjETP9Ar9oCGCy8KKTNmzt72PCT7Ww/1kpaShJr3zGPkz39PPzCYR7cFLjYOdoQfoW5iEx10z/Qj22GOSsgc9a4m3r7fGz4yXZ21Xq4/8YV/J/zF1CQFbjXZ73Hy1Pbq+nt93NeWUG0Sy0iEnHTL9A9tdB2LPCzc4Eui6tuG3c35xxfeGon24+18tAd53P9yuHzrszLz+BT71oajRKLiMTE9Av0XU/Bs/cPX7b4ynF3++ZzB3n6jTq+sHbZKWEuIpIIpl+gv+P9MP+8t5+nZEDpmtPu8sS2ar71h4N84IJSPv7OJVEuoIhIfEy/QC9YGPgXol++Xsu9P9/JFUuL+Mf3r9SNm0UkYSXG0P8x/G5XPZ994g3WlM/mkb+o0PS2IpLQpl8NfYS2rl6y01NITQ6EtXOOt5pOsmnfCb7+u32cW5rPD+66kMw0dTsUkcQ2LQO9u9fHb3cd5/Ft1Ww90kJykjE/P4MFBZlUtXRx3OMFYPXCAn541xpy0qfl2xQRCcu0S7rHt1bxjxv30uHtp7wwi79691J8fkd1SxfVrd2cv3AWl55ZyGVLilhUmKU2cxGZMaZdoJcUZPLu5XO55cIyLlo8W4EtIhI07QL9yrOKufKs4ngXQ0RkylG3DxGRBKFAFxFJECEFupmtNbP9ZnbIzO4bZX26mf13cP2rZlYe6YKKiMjpjRvoZpYMPAisA1YAt5nZihGbfRhodc6dCTwAfD3SBRURkdMLpYa+BjjknHvLOdcLPA7cNGKbm4AfBX9+CrjG1P1ERCSmQgn0BUD1kOc1wWWjbuOc6wc8QOHIA5nZBjOrNLPKxsbGiZVYRERGFdOLos65R5xzFc65iuJidT0UEYmkUAK9Figb8rw0uGzUbcwsBcgHmiNRQBERCU0oA4u2AUvNbDGB4L4VuH3ENk8DHwS2AH8OPO+cc6c76Pbt25vM7Fj4RQagCGia4L6JROdB52CAzsPMOQeLxloxbqA75/rN7FPA74Fk4FHn3G4z+ypQ6Zx7GvgB8BMzOwS0EAj98Y474TYXM6t0zlVMdP9EofOgczBA50HnAEIc+u+c2whsHLHs/iE/e4EPRLZoIiISDo0UFRFJENM10B+JdwGmCJ0HnYMBOg86B9g41y5FRGSamK41dBERGUGBLiKSIKZdoI8382MiMrMyM9tkZnvMbLeZ3R1cPtvMnjWzg8HHWfEua7SZWbKZvWZmvw4+Xxyc4fNQcMbPtHiXMdrMrMDMnjKzfWa218wumWmfBTP7TPB3YZeZ/czMMmbiZ2GkaRXoIc78mIj6gc8551YAFwOfDL7v+4A/OOeWAn8IPk90dwN7hzz/OvBAcKbPVgIzfya6bwG/c86dDZxH4HzMmM+CmS0A/h9Q4Zw7h8D4mFuZmZ+FYaZVoBPazI8Jxzl33Dm3I/hzB4Ff4AUMn+XyR8D74lPC2DCzUuAG4PvB5wa8i8AMnzAzzkE+cCWBwXw453qdc23MsM8CgTE0mcGpRrKA48ywz8JoplughzLzY0IL3jxkNfAqMNc5dzy4qh6YG6dixco3gS8A/uDzQqAtOMMnzIzPw2KgEfjPYNPT980smxn0WXDO1QL/ClQRCHIPsJ2Z91k4xXQL9BnNzHKA/wH+yjnXPnRdcO6chO2DamY3Aiecc9vjXZY4SwHOBx52zq0GTjKieWUGfBZmEfhGshgoAbKBtXEt1BQx3QI9lJkfE5KZpRII8/9yzv08uLjBzOYH188HTsSrfDFwGbDezI4SaGp7F4G25ILg126YGZ+HGqDGOfdq8PlTBAJ+Jn0W3g0ccc41Ouf6gJ8T+HzMtM/CKaZboA/O/Bi8gn0rgZkeE1qwrfgHwF7n3DeGrBqY5ZLg4y9jXbZYcc590TlX6pwrJ/D//rxz7g5gE4EZPiHBzwGAc64eqDazZcFF1wB7mEGfBQJNLRebWVbwd2PgHMyoz8Jopt1IUTO7nkBb6sDMj/8Y5yJFnZldDrwIvMnb7cd/TaAd/QlgIXAMuNk51xKXQsaQmV0FfN45d6OZnUGgxj4beA240znXE8/yRZuZrSJwYTgNeAv4EIHK2Yz5LJjZV4BbCPQAew34CIE28xn1WRhp2gW6iIiMbro1uYiIyBgU6CIiCUKBLiKSIBToIiIJQoEuIpIgFOgiIglCgS4ikiD+PwXEBBcYIEp9AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yYoKb71mQ__V"
      },
      "source": [
        "from keras.models import load_model\n",
        "model=load_model('best_model.hdf5')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kf5MUepiRDQ8"
      },
      "source": [
        "def predict(audio):\n",
        "    prob=model.predict(audio.reshape(1,8000,1))\n",
        "    index=np.argmax(prob[0])\n",
        "    return classes[index]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M89hbCfGRF5k",
        "outputId": "459908f3-6647-489b-a96f-034aa68843bc"
      },
      "source": [
        "import random\n",
        "index=random.randint(0,len(x_val)-1)\n",
        "samples=x_val[index].ravel()\n",
        "print(\"Audio:\",classes[np.argmax(y_val[index])])\n",
        "ipd.Audio(samples, rate=8000)\n",
        "print(\"Text:\",predict(samples))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Audio: Kalubowila\n",
            "Text: Kalubowila\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "TnvAxCaWSI9X",
        "outputId": "d0d1a193-0b3b-44c4-d9b6-a3e186551353"
      },
      "source": [
        "\n",
        "filepath='/content/MagesticCity.wav'\n",
        "\n",
        "#reading the voice commands\n",
        "sample, sample_rate = librosa.load(filepath, sr = 16000)\n",
        "sample = sps.resample(sample, 8000)\n",
        "ipd.Audio(sample,rate=8000)  \n",
        "\n",
        "predict(sample)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'MagesticCity'"
            ]
          },
          "execution_count": 43,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    }
  ]
}