notebooks/keyword_mlp_tutorial.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Keyword_MLP_Tutorial.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2TvhbFZpR0dz"
      },
      "source": [
        "# Keyword-MLP Tutorial\n",
        "\n",
        "This notebook will guide you through the steps to training and running inference on Google Speech Commands V2 (35) with the [Keyword-MLP](https://github.com/AI-Research-BD/Keyword-MLP.git) repository."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ktCvR-FJT9Zl"
      },
      "source": [
        "## Setup"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UTOUEB7VR_co"
      },
      "source": [
        "### 1. Clone the repository"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FpEyVD_pRsLK",
        "outputId": "55c38e75-26b5-445c-95a7-a7981f0a4285"
      },
      "source": [
        "!git clone https://github.com/AI-Research-BD/Keyword-MLP.git"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Keyword-MLP'...\n",
            "remote: Enumerating objects: 44, done.\u001b[K\n",
            "remote: Counting objects: 100% (44/44), done.\u001b[K\n",
            "remote: Compressing objects: 100% (37/37), done.\u001b[K\n",
            "remote: Total 44 (delta 5), reused 30 (delta 2), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (44/44), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oMyHNXrDSId5",
        "outputId": "1c30638e-dca6-4ccc-ac47-4d94be721027"
      },
      "source": [
        "cd Keyword-MLP"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Keyword-MLP\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8V1TojnpSNKO"
      },
      "source": [
        "### 2. Install requirements"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pYxEu6sUSJGw"
      },
      "source": [
        "!pip install -qr requirements.txt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P3vqXzDSSdsW"
      },
      "source": [
        "### 3. Download the Google Speech Commands V2 dataset\n",
        "\n",
        "We'll be saving it to the `./data/` folder."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kyTh1owVSeoa"
      },
      "source": [
        "!sh ./download_gspeech_v2.sh ./data/"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xqgYjtHXSslk",
        "outputId": "f6eff51e-6b56-49a9-bf2c-7a18ea0e1c82"
      },
      "source": [
        "!ls data"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "_background_noise_  five     left     README.md\t\ttree\n",
            "backward\t    follow   LICENSE  right\t\ttwo\n",
            "bed\t\t    forward  marvin   seven\t\tup\n",
            "bird\t\t    four     nine     sheila\t\tvalidation_list.txt\n",
            "cat\t\t    go\t     no       six\t\tvisual\n",
            "dog\t\t    happy    off      stop\t\twow\n",
            "down\t\t    house    on       testing_list.txt\tyes\n",
            "eight\t\t    learn    one      three\t\tzero\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "leL0YA9STIua"
      },
      "source": [
        "As you can see, the dataset provides a `validation_list.txt` and a `testing_list.txt` as the split. We'll run a simple script `make_data_list.py` to also generate a `training_list.txt`, as well as a `label_map.json` that maps numeric indices to class labels."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TdRfkTruTFCn",
        "outputId": "d2903bc3-81ac-4dd2-f4ce-7fa61046abc5"
      },
      "source": [
        "!python make_data_list.py -v ./data/validation_list.txt -t ./data/testing_list.txt -d ./data/ -o ./data/"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of training samples: 84843\n",
            "Number of validation samples: 9981\n",
            "Number of test samples: 11005\n",
            "Saved data lists and label map.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-fSPsrlIUAEz"
      },
      "source": [
        "## Using Pre-trained Models for Inference\n",
        "\n",
        "The Keyword-MLP repository provides a pretrained checkpoint. We can use this checkpoint to run some inferences, before we look at training."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YKsEVk9PUbhf"
      },
      "source": [
        "### 4. Downloading Pre-Trained Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c71a6WbzUEUB"
      },
      "source": [
        "!wget -O \"kwmlp_pretrained.ckpt\" \"https://drive.google.com/uc?id=1lywXTaJjPud41f3G_NmuRHzhDY8uNbWe&export=download\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hlJ8T_JKWY_1"
      },
      "source": [
        "### 5. Exploring Some Test Set Audio Files\n",
        "\n",
        "Let's take a few files from the test set, take a look at their melspectrograms, and listen to them."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A04iDUBI6oa3",
        "outputId": "8978212b-e8f6-4d53-a435-44b413a4386e"
      },
      "source": [
        "with open(\"data/testing_list.txt\", \"r\") as f:\n",
        "  test_samples = f.read().rstrip().split(\"\\n\")\n",
        "\n",
        "samples = test_samples[:3]\n",
        "print(samples)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['./data/left/5828dfa2_nohash_0.wav', './data/down/cfbedff9_nohash_3.wav', './data/one/fb7eb481_nohash_3.wav']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ozp0d7YCWNBP"
      },
      "source": [
        "from IPython.display import Audio\n",
        "import matplotlib.pyplot as plt\n",
        "import librosa\n",
        "\n",
        "def show_melspec(audio_path):\n",
        "    print(f\"Showing {audio_path}\")\n",
        "    audio_settings = {\n",
        "        \"sr\": 16000,\n",
        "        \"n_mels\": 40,\n",
        "        \"n_fft\": 480,\n",
        "        \"win_length\": 480,\n",
        "        \"hop_length\": 160,\n",
        "        \"center\": False\n",
        "    }\n",
        "    x = librosa.load(audio_path, audio_settings[\"sr\"])[0]\n",
        "    x = librosa.util.fix_length(x, audio_settings[\"sr\"])\n",
        "    x = librosa.feature.melspectrogram(y=x, **audio_settings)      \n",
        "  \n",
        "    plt.figure(figsize=(7, 5))\n",
        "    plt.imshow(x, cmap=\"hot\")\n",
        "    plt.show()\n",
        "\n"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        },
        "id": "I-nqPIZLWN0f",
        "outputId": "cd9a295e-f0c6-48a6-e102-61cc94ae3429"
      },
      "source": [
        "show_melspec(samples[0])\n",
        "Audio(samples[0])"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Showing ./data/left/5828dfa2_nohash_0.wav\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 504x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ],
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        },
        "id": "lZVIxsXrXJpF",
        "outputId": "b0483a31-1d58-4c6f-ed93-42c3b474295b"
      },
      "source": [
        "show_melspec(samples[1])\n",
        "Audio(samples[1])"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Showing ./data/down/cfbedff9_nohash_3.wav\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ULyRdavvU+t/x7/cfx18XhnonCdvvUdUXmJC0OSJuGtrGR5Dtt0q6V9IjeqWP8klVfai7JL1B1eNLro2II7MyyBFg++2S/jYirrZ9tqozqiWSHpK0LiJemM3xlcr2haq+YLJA0uOSPqzql1qOvQ7Y/rSkD6j6Nu5Dkv5CVc+J469D3OoIAFAkviQBACgSAQUAKBIBBQAoEgEFACgSAQUAKBIBBQAoEgEFACjS/wMiLpFsx2ScVAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 504x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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AAAAEA///+////+v////3/9//7//z//v///wcAAgAIAAYABQAGAAUACAACAAkAAAABAPv//v/7//v/+//4//r/AAD+//P//P/6//r/+//6//z//P8GAAYACgAHAAAAAgADAPz/+//5//f////+/wIAAAABAAEAAQADAAYA/P///wMAAAD+//z/AgD9//7/AQAIAAYABQAJAAwACwAGAAoACQAIAAgAAwAGAPf//f/8//z//P/6//z/AgADAAEA/v8BAAMA/P/1//r//f8GAAwACQAMAAsABwAMAAUAAAAFAAcAAwD9/wUAAwADAP7/+v8BAAcACwANAA8ADQAQAAgACQAMAAUABgACAAYAAQAAAPr/+//6//b/9//5//r/8//2//r/+P/6////AAABAAEA///6//r/+f/2//b/+v/0//X/7//1//H/9f/3//b//f/2/wAAAgD///7////6//z/AQD9/wAABQAAAAEAAwADAAIAAQAIAAQABQD//wgABgAIAAIAAwD//wYAAQD//wQA+f8CAPr/+v/5//z/+v8CAAIA/f8CAP7/BAADAAgACgAFAA0ACQAKAA0ADgADAAMAAwAAAAAA+P/7//3//P/+//3/AQABAAUADQAKAAMABQADAAYABQAEAAYAAgAGAAIA//8AAP/////9//j/8//3//7/+P/4//b/+v/7//z//P/7//r//v/1//j/+v/w//n/+f/2//n////9//7/BwADAAAAAQD7//7/+f/5////AQACAAAAAgAAAP3/AQAAAAMABgAJAAcABwACAAIAAAD+/wEAAgD//wUAAwD9/wEA/v8AAPr/+//3//r/+f/9//f//P8BAAMABgABAAEA///6//v/+v/4//z//P8AAP3///8EAP7/AgADAAUABgADAAcABQAPAAQADAAJAAUACwAJAAIABgAGAAkABAD////////+/wEA//8BAAgACQAKAAoAEgASAAwACgALAAIABQD6/wIAAgAAAP3//v/6/wEABAAIAAMACgAIAAcACAALAAYABAAHAP7/AAD8//7/+/8AAAEABAAEAP7/+v////7/+//9//7//v8BAAEAAQADAAgAAQD3//v/+P/1//X//P/3//j/+//+////AgACAAQABQAAAAAA//8GAP//AQABAPz/+P/5//3/+v/+/wAA+/8FAAMAAgADAP7//P/6//3/9P/7//r//P/6//7/AQADAAAA/v/6////BwAEAAEAAQD+//7/AQAAAAYACAAFAAcADAAGAAcABQADAP7/+v////n//v8BAAMA/P/9/wIA//////7/AAAAAPz//P/5////+////wEA/v/+/wUACAAEAAYAAAAEAP3////+//z/AwABAP//BQAEAAQAAwACAPz////9//v/8//2//3////9//r/+f/8//f//f/5//v//f/+/wAA/f8DAAQAAAD+/wAA/P/6//r/+f/3//X/+//4//z//P////7/AgAJAAsACQAJAAsABgALAAQAAwABAP//BQADAP3/+//5//j/8P/z//j/+P/+/wAAAAAAAAsABAADAAYACAALAAAAAwD+//7/+//7//7////7//r/+//6/wEAAAD6//3/AAAEAAAABAAJAAsACgAKAAsACwAKAAMAAgD8/wUA//8BAAIABAAHAAQABQAFAAcADAAMAAYACQACAAIA/v8EAAgAAgD8//r/9//x//P/8P/x//L/9//7////AgD9/wMAAAAIAPz/AgAAAAEAAwD8//v//v/7//j/BgD6//j//v/+/wMAAAAEAAUA/f8DAAIA/v8EAP///P/7//b/+f/z//r/+v/5//n/+//5//n//f///wEA//8HAAUAAQD//wEA/P/4//X/9P/6//z/AgD9//r///8FAP7/BAAAAP7////6//z//f/9//////8CAAAAAAAGAAQAAQAAAPv/AAD9////AgD7/wMADQAOAAwACgAKAAoABgACAAQAAwACAAgABAAHAAYACQAGAAIAAwAAAPz/AAD8//r//v8AAAUABgAHAAYAAwAAAAAAAgABAAQABgAJAAcACwAMAAcABQADAAEA+//4//b/9//1//f//P/+/wUACwAMAAsACgAEAAMABQABAAEAAwADAAEA+//7/wEA/f8AAP7/+f8AAPz/8v/z//T/8v/4//L/9P/1//r/+f/1//r//P/6///////+//7/AAD8//7/AQADAAMA/v/+//v/+P/4//z//f/1//7/+f/7/wEA/v8EAAYAAQACAAMA/v//////AQD7//3/AwD9/wAAAwD4//n/+//7//n/+f/6//f/+P/8/wIAAQABAAMABQADAAUAAAD8//7/+v////7//v/7//3//v////7/AgAIAAUACQAJAAkABAAGAAgAAwAGAAQAAwD+//7///8AAAEA/v8FAAQACAAMAA0ABAAHAAgAAAAJAAgABQAGAAAA/f/4//r//v8DAAQA/f8CAAAAAgACAAQABgAGAAUADAALAAYABgD//wEA9//8/wIA+/8BAAIAAwAAAAMAAgD8//z//P//////AAD///7//v/6//z/+f8DAP//BgACAAIAAwACAAAA//8FAAUABQAEAAcA///6//v/+v/3//f//P///wMAAgABAPz/+f8DAAIABAAFAAMA/v///wEA/v8BAP7//v8HAP//+v/8/////P8BAAMABQAGAAcAAwAAAAIA/f8BAP//+v////n/+//8//3//f/+//3/AQD+//X//f/5//3//P/9////+//7//3/9v/2//v/9//0//r/9f/+/wEAAAD+/wAACQAFAAcACQAGAAoABwAEAAcAAwD5//7//v///wEAAAAFAAUABwALAAcACQALAA4ACAADAAUABAABAP3/AAABAPv/+/8DAPn/9f/7//v/+P/5//3/AQACAP//AwD+//j//v/8//X/8//4//z/9//8/wAA/P8BAAEAAgAEAAAAAgAIAAEAAAAGAAUACwAOAAgABgAIAAcA/f/8//j/+P/8//b/+f8CAP//+f8CAAIA/v8DAP///P/5//z/+f///wEA/P8CAAIA/f/5//z/AAABAAEAAwAFAAQABAABAAgACAAJAAkADQAHAAcABwAFAAMA//8FAAUAAAD9//3//v8CAAEABQALAAYABgAGAAEA///+//3////2//n/9//8//z/9/////7/AgD9//7/AQAAAP///P8CAAMACAAGAAcABQD8/wMA///4//H/8//y//D/7//0//r/+v/6//f/+//6//3///8EAP///f8EAAMAAQACAP7/+f/7//r/+P/1//X/+P/4//n/AAACAAIA/f8AAAgA///8/////f/6//z//f/7//7//f8CAAAABAAAAP7/AwAAAAIAAAABAAAACQAHAAsACQABAAcABQD9////BAD8/wAA///9/wAA///9/wEACgAOAA4AEAALAAgABwABAAYA/v/2/wMAAwD9////BwANAAcABwALAAsACgAKAAoADgAIAAcACQAEAP3///////j/+//+/wMA///7//r//v8CAP3//////wEA///+/wIA/f/+////+//2//j//v/3//n/+f/6/wAA/v/6/wMAAQD9/wIA/v/5/////f/8//n/+v/8//f/8//y//b/8//z//b/+////wEACQAFAAYACAAHAAgABwAIAAcABQAFAAIA/f/6//r/9v/y//T/8//z//X/9v/6//z//v8FAAUABQACAAQABwACAAEABgD7//z/+//7//z/+f/9//v/9//8/wEAAwABAAIADAAHAAkADAAQABAACgAMAAwACwAHAAQA/v8DAAQACgAHAAUACgAJAAoABAAMAAwABQAJAAwACgAHAAcABQACAP3/AAD4//v/9//1//j/9v/z//P/+//9/wAA//8DAP7//v8CAAEA/P/9/woABAADAAAAAgAAAPf/+v/7//v//f///wQAAQD//wUABgABAAYACAAFAAQACAAEAP//+//+//z/+f/4//j//P/9//n/9//5//n/+//9//7/+f/+//3/9v/3//X/9v/s/+3/6//u//P/+v/+////AQAFAAMAAQAFAAcABQAHAAYAAgD//////v/8//r/+//9////+/8DAAQA//8HAAYACAAHAAQABAAEAAQAAwAAAP3///8AAPz//P8CAAEAAwAIAAoABwAHAAEAAwAAAP7/AQD+/wAAAwAEAAEA/P8EAAIAAwADAAAAAgAHAAEA+f8EAAEACAD9//v/AAAAAAUABQABAAMADAAOAAoADQALAAoADQAJAAMABAAGAAAA9//6//j/9v/3//b//P/8/wMABwAGAAcABQAHAAUABwAEAAEA/f/2//b/+//9//v//P////j//P/4//j//v8AAP3/+//6//v/9//3//T/8v/1//X/8//3//b/8P/3//b/8v/8//r///8CAAQACgAFAAoABwAHAAgACAALAAYABgABAPz//P8AAP3/BQADAAAABgADAAMACwAOABUADwAMABQACAAKAA0ADAAMAAsABQAIAAIA/f/8//v////6/wIAAQD9//b/+//+//3/AQAHAAUACQAHAA0ACwAJAAgABgACAAcA//////7//f8EAAcABAACAAcABwAIAAkABgAFAAMABQABAAIA+v/9//v/+//6//z//P/7//b/+f/7//r/BQAEAAYAAwD//wMA/v/6//T/9P/0//D/8f/x//H/7f/u/+//7//y//b/8v/3//X/9f/u/+3/8f/z//T/9P/8/////f/9//7/+//8//f//P/4//j/9f/+//f/+/8CAPn/+v/7//z//v/+/wIAAwD9//n/9P/5//z/+//6//z/AQACAAQACgANABQADwAOAAoADQAIAAgA//8CAAMAAAAFAAgABwAHAAoACwANAAsADwAQAAkABwAIAAkABAD9/wEABwAGAAkADQALAA0ADwALAAwAEwAOAA0ACQAHAAcAAQD3//v/+//z//f//////wYAAwAJAAYAAAAEAP7////+//r//P8EAAMA//8DAAcACAAHAAYABgAEAAcACAAAAAAA9v/6//r/9f/4//r/AQABAP7/AwD2//f/9//0//j/9P/3//P/9f/z//X/9P/1//j/+v/7/wEAAQD8//3////+//r/+P/8/wAA+v/6//z/+P////z/+v8BAP//AAAIAPr//f8CAPv//P/+//r/9//6//r/+v/5//P/8//z//f/9P/7//z/+f/8//b/9v/3//z/+v/8//3/+f///wAA//8CAPr//v///wEAAAD8/wEA/v8AAPz//f/6//z/+//2//7//f/7/wEA///8////+//6//r/9//9//z//v///wEABwAMAAgACwAJAA0ADQAGAAkACgAIAAUACQAIAAIAAwD/////AgAGAAoACgAKAA0ACwANAAMAAwABAAYA//8AAAEA/P/8//3/AgABAAcABAAGAAYACgAIAAwACQAFAAUACQADAAMABAACAAoABAD//wIAAQD///z////7//b//v8AAP////8CAAcAAwABAAQAAgACAAIA+f8AAP7//P/3//j/9P/0//v/9P/4//f/+v/7/wQA/f8BAAEAAQAEAAMAAQACAAQABAABAAgABgACAAIAAAAEAAMA/v/9/wMABAALAAgAAwAGAAMA/f/5//r/+//1//T/9f/9//7/AAAGAAUACAAJAAcADQAIAAcAAgADAPz/+v/6//r//P8GAAIA//8AAPn/+//+/wAA/P/9//v//v8HAAgACgAIAAoACAAEAP7/+//8//n/+P/3/wEABQD+/wAABwADAAAABQADAAEA+v/2//b//P/y//P/+v/z//b/+f/4//r/9v/6//f/9v/4//j/+//8//v/+f/9//b/8v/1//T/9P/x//f/9v/5//j/9f/2//r//P/8/////v/5////AAD9/wcAAQAFAAcA+v/6//j/9v/6//v//f/7//v/BAABAP3/+f/8/////v/5//3/AAD///v/BgACAAIABQAEAAsABgAGAAYAAgD+/wMAAwACAAEAAgAIAAMACAAIAAgABwAHAAkABQAFAAEA/v/7////AwD+/wkACAAIAAkACAAIAAcACgAOABEACgAMAAsADQAJAAYABQD///3/AAD///7/AAD+//j//P///wQACgAGAAcACQALAAcAAwABAP3/+v/+//b/+P/7//v//f/9//r/+////wMABgABAAQAAgAGAAMACQAHAAMAAgD5//X/8v/z//P/9//s//H/9P/v/+//7//0/+//+f/5//r/AAAAAP///v////3//f/6//z//f/7//7//P////7/AAABAAIABQAEAAUAAwAJAAYA/f8BAAUABwACAAMA//8EAAMAAgD//////f/9//7/+v/7/wMABQABAAMABgABAP//AQAFAAIA+v/8/wYA+v/5//r//P/5////AwD///3/AgADAPv//v/8/wIABAD//wUAAAAGAAIAAgAGAAMABwAGAAYABgAGAAMAAgADAAQABwAJAAoABgAHAAcACAAGAAcACAAJABIADQALAAsAAgAEAAUABAAHAAYABQD9//3/BAAAAAUABgAGAAgAAQD8//n/9v/1//j/+f/1//7//////wAA/v8CAAEABQAFAP3//P/7/////P/6//n/+f/9/wAAAAD8//j//P/5//r/+f/4//7/AAAFAP//AAAEAP7/AQACAAAA/v8BAPv//P/9//r/+v/5//7//f/9//7/AAD3//j/+f/6//v/AAD6//n//P/8//7/+v8AAAQA/v///wIA+v/+/wIABAAHAAQAAQACAAgABAAJAAUABAABAP3//P/9//r////+//3//v/w//T/8//2//f/+f/6////+/8AAAYABAAIAAcAAwAJAAcAAwAGAAEAAQABAPv//f8BAAMAAgD+//v//v8BAAQAAgADAP//AQD+/wMAAAD///z/9v/5//j/9f/1//b/8P/3//r/9//5//n///8EAAAA/P8AAPv/+v/5//f/AAD5//v/AAD+////+//3//f/AgAGAAIAAQABAAQABAABAP7/BAAAAP//AwABAP7/AAD2//f/+f/2//v/+f/+//z/AgD+//7/AAAIAAQABwAGAAQABwAAAAIAAgD//wYAAQAGAAgABwAFAAUADAAMAAwADAAMABAAEgAWABIACgALAAsACwAIAAYAAQD+//7/9//5//r/+v/8//v////8/wIA+//6//7//P8CAPr/+//7//n/9v/2//T//P////z/+v/5//z/AAABAAEABAAGAAIAAAABAP7/+f/0/+z/7P/v/+//7P/v//X/9//5//f/+/8AAAUAAAD6//n//f////T/8//1//X/9P/1//L////7//7//f///wQAAgAEAAMABQAGAAoABQADAAIA//8CAAAABQAJAAoACQALABIAFAAPAA0ACAAJAAcABAAJAAUABwAGAP7///////r////+/wEABgAEAP//AgADAAoAAwABAAUAAgAEAAYABQAEAAcABQAEAAEABwAEAAQAAAABAAMAAAD7//r/AwAEAAYAAgAGAAIABQAEAAkACwAEAAIAAAAAAPv//f/6/wMA+//5////+P/9//r/+v/4//f/+f8BAP7/+f/8/wEABgD+/wIA+f/3//n/9P/8//f/+f/5//v//P/4/wIAAgAIAAYACgALAAwABQAHAAEAAwADAAIAAAD7//X/8f/1//j/+P/7/wIAAQAAAAAAAwAGAAQACAADAAMAAgAAAPj/+f/7//X/9v/9//7/BgACAP///v8DAAIAAgAGAAgABQAEAAQABAACAAEA/f/4//r/+//+//r//v/+/wMAAQACAAMABAAJAP///f/6/wUAAgAAAAQA/v8CAP7//v8IAAQACQADAAgABQAEAAQA/f/3//f/+//6//P/8f/5//j/+f/4//7/AQAEAAYACgARABEAEQANAAwACQAOAAkABwAKAAUABwAGAAUABAADAAUAAwAHAAQAAwADAAMAAAD1//v/9//6//j/+f/8//f/+f/4//n//f/+//j/+//9//n//v/5//z////8//n/9//1//H/9P/z//j/+//6//r//f/+//f//f/7//7/+f/5//f/9v/4//P/+f/2//v///////v/+f/7/wEAAwD+/wMAAQD7//n//P/+//7/AgABAAQAAwD//wIAAgACAAEABgAIAAcAAwABAAAA//8BAAIA///9//r/9//3//7//f8DAAYAAgAIAAoACAADAAIAAAD/////AgADAAYAAAACAAUABwAGAAkADAAMAAcACQANAAsACAAHAAkACwACAAUABQAHAAIABAACAAAAAQD9//7/AgAGAA0ADAAMAAcABwABAAQAAwAEAAkABAAAAPz/+//+//3/+f/4//j/+f/4//L/9P/5//P/9v/4//z/AwD///7/+//7//n//P/9//3/+f/6//n/9v/2//L/+f/6//n/9//7//z/8//3//j/9v/1//n/AAD7////AAACAAUAAwAFAAgAAwACAAoACAAGAAUAAwD9//n//P8EAP///v/+/wAAAwABAAYADwAPAAgABgAHAAcACAAIAAkACwABAAIAAQAAAP3/+f/9/wEAAwAAAAYACgAIAAkABQAHAAYABgACAAIAAAABAAAA//////7/9v/2//v//P/5//z//v/+/wEA////////+//6//z/+//3//r/+f/0//L/+P/6//f/+f/6//v/+v8AAAEABgADAAAABwAFAAEAAQADAAIAAgD9//b/+v/4//T/6f/v//T/+f/6//r/AgD+/wQABgAHAAQA+v////v/+f/8//r//f////z/8//2//f/9P/2//j/+v/+/wAAAQD9/wEAAAAAAAgAAwAJAAcAAgABAPj//P/0//j/AgACAAEABAAFAAAA/f8FAAIABAD//wYAAwD9/////f8AAP//+v///wAAAQD7//b//v/+//7//v8BAP//AAD+//v//v/6//r//v8EAA0ABwAJAAwADwAPAA0AEQAOABEADQAKAAoABgAJAAUAAwACAP//BQADAAEACAABAP//AQACAAEAAgAHAAIA///+///////+/wMA/P/4//7/+f/8////+/8AAP//AAACAAIAAwAFAAMABAADAAQABQADAAUAAQAHAAoABwAEAAMACAAFAAUAAAAFAP///P///wAAAgAFAAcABgAIAAoABgAGAAcAAwD9//v///////X/9v/3//H/+//6//j//v/5//j//v8BAAEAAQAEAAMABQABAAIAAQACAPv/+/8BAPz/9//4//j/7//0//j/+v/5//z/BgACAAUACAALAAgABgABAAEAAgD6//v/+f/5//z//P/6/////P/+//v/AAAFAAAAAQADAAIACgAFAAYABAD//wUABAACAAIA/v8CAPz/+v/6//3//P/7/wAABAD+//7/AAD+//z/BgADAAcACQAJAAgABgAFAAcAAgADAAMABQD///z/+P/5//z/9//5//v//f/6//v/+/8CAP//AQD3//z/+v/7//v/+P/1//T/+//7//3//P8AAAQAAQADAAUACwAJAAcABQAGAAQACgAJAAcABAACAP3/+v//////+v/3//z/+v/2//r/+v/6//v/9f/3//n/AgAAAAAAAwD+/wEAAgABAP7/AgAEAAUAAwACAAQAAwACAAQABQAGAAsACAALAAgACAAFAAQA//8BAAAA//8AAAYAAgADAAcAAwALAAYABQAJAAUACwALAAkABwD///7////7/wAA9//3//P/9v/1//r/9f/2//r/+P/2//r/+//5//r//P/6//7/AQACAPn/+//+//z/9//5//z/+v/5//b/8v/1//P/9f/4//v/+//4//P/+v////r/+v/8//3/+v/8////BQADAAYABAAAAP7/+f/7//v//f/+/wEABwALAAwACAAIAAgADAAEAAcABAAFAAcAAAD///z/+//+///////8/wIA/f8CAAEAAgAHAAYAAwABAAcABwABAAAAAAAFAAAAAwAAAPv/+f/9/wMAAAAAAAQACgAIAA4ADgALAAkABgAJAAIABAAEAAEABgACAAYACQAFAAIA/v8KAAgABQADAAcA/P/+//7////8//j//P/8//7/+v/7//P/8f/w//X/8v/5//f/+/8DAAcADwAMAAMACAAKAAkA///9////+P/w//T/+f/z//P/9v/7//f/+//3//z//////wsACwALABAACAAGAAkA///9/wEA///+//7/+f/6//j//P///wEABQAPAAsACwAOAAYABAACAP///P/2//j/8f/0//P/7P/x/+3/8P/y//r//v/9//3/AwALAAgACQAIAAQACAAFAAUA/v/6////9f/0//v/9f/4//r//v8FAAcABQALABEACgAFAA4ACgADAAYAAwACAPz/+P/8//j/+//8/wAA/P/7//3///8AAAIABQAEAP//BgACAPr////6//b/+//6//n/+v/5//z//P///wMABwAHAAsADwALAA4AEAAKAAkAAwADAAMAAgAAAAEABAD///r/9//2//3//f8BAAUAAgAAAAMA///8//3//f/8//z/+P/3//v/9P/8//7//f8AAAEAAwD+/wAAAgABAPn////8//r/8//y//b/9f/1//b/+//6//v/+v/4//3//f8EAAMAAwAEAAYAAwACAAEA+v/7//n/9f/v//X/8v/5//f/+v/7//r//f/7//3//P8AAAUABAABAAwACwAJAAsACAAIAAQA/v/9//z/+f/6//3/+/8CAP//+P8DAAIABgAHAAoACwAIAAsACAAJAAUABwAIAAoADgAKAA0AEQAQAA4ADwALABAADQAOABYAFAARABAAEQAKAAUACwD//wUA/v/9/wAA/f8FAAMABQAJAAYABAAFAAMAAgACAAgABQD+//n//P/1//f//P/2//b/+P/7//X/+f/1//P/8f/0//X/+P/4//r/+P/4//P/9P/4//H/9f/1//f/9v/7/wAA///9//n//P///wIA/P/5//v/+v/z//f/+f/4//f/8//4//f//f/9/wUABgAEAAoABAAIAP//+v8AAPf/+f/4//r//v/6//j/+P/7//7/AwAEAAUACwALABIADgAHAAwADgAHAAcABQAFAAQABQACAAAA+//2//P/9f/0//X/+P/6//3//v8EAAwADAAOAA4ADgAMAA4ACAAHAAMA/f/5//3/+v/7//z///8DAAQABwAEAAcACQAEAAgABgAFAAEABAAGAAQA//8IAAAA//8BAAAAAwD+/wYABQAHAAkADQANAAsACwAGAAYAAAD4//f/9P/w/+r/6//u/+r/6//q/+7/7v/2//b//v8BAPj////+/wIA//8CAAEA///7//T/9v/v/+v/6//n/+z/6P/o/+//7P/0//P/9v/5//v//f/+//f/+P/5//T//f/4//f//f//////AAAAAAIAAwAHAAkABwAMAAkACwALAAcA/f///wMAAQABAAEA//8AAPz///8AAAAA/v8AAAUAAwAEAAkACAAKAAgAEAAWAA4AEAAKAA0AAwAGAAUAAQAEAAIABQAAAAIACQAMAA8ADgANABIACgALAAoACQAJAAYABgACAAUABAD///r/+P/1//D/9P/3//b//P///wUABQABAAUAAwAGAAIACQADAAcAAQD/////9v/1//T/+f/5//r//v/7/wAA+f/+/wQA/v8DAAAAAwD///z////8//v/9v/1//L/8f/x//P/8//2//n/+//+//3/+//2//7/+P/6//z/+v/8//b/9P/2//f/9//4//f/8v/3//b/9P/3//b//v//////BwAHAAsADgANAA8ADgAPAAkABwAHAAcABAAGAAIAAwADAAMAAgAGAAUABAANAAkACAAKAAgACgAJAAsABQAEAAQAAgD//wIABQADAAUACAALAAgACAALAAgABwAGAAoACgAJAAoABAAHAAcAAgAAAPn//P/4//z/+f/6//v/+P/5//3//v/+/wMAAwACAAEA/v8AAP7////3//z//P/+//z/9//9/wAA///8//r//v/5//z//P/8/wAA+f8CAAIA/v/7//r/+v/3//f/+f/6//v/+f/1//f//P/6//n/+P/7/wAA/v/7//3////5/wAA///9/wMA/v8AAPz/+v/6//f/9v/x//T/7//x//D/7v/0//X/+f/6//z/+v///wAAAQAIAAkACAAKAAcADAAHAAkABQAEAAAABwAEAAkACQAFAAQABwAHAAUABwAFAAkACAAFAAsADwAIAAoAAAD9//j//v/8//n//P/5//j//f/7////AQAHAAoACQANAA0ACgALAA0ACQAGAAUAAwD9//f/+v8CAP///P8AAAQAAgAKAAYABQAAAAMACAABAAUABwAEAP7/AwAIAAcAAAD+//z/+f/2//X/+f/0//j//f/5//v//v8EAAUABwAJAAcACgAIAAIA+//4//r/+f/4//v/+//5//n/8//x//D/7v/w//P/9P/2//3/+//4//n//P////3/+f/1//z//v/9//7/AAAEAAUACAAIAAcACAAGAAgABgAGAAMACgAFAAgAAwADAAQAAwAGAAAAAAABAP/////+//3//v8IAAYAAAAHAAQABwAEAAQACQAEAAcABQAFAAYABgAAAPv/+v8CAAAA+//5//j/+f/1//v//P/6/wAAAQD//wQABQADAAYACgAFAAQA/v///wAA/P/9//z//v/3//3////3//n//P/7//b/9v/5//b/+v/7//3//f/7/wIA///+//7/BQACAP3//v8AAP7/AQACAAAAAwD//wMA///9//3//f8FAAIA/P/+/wAAAwD//wMAAwADAAYACAAMAAoADwAJAAoABQAHAAMABAAAAAEAAAD5//3////9/////v8CAPz/+//9//z/+v8BAAIAAAAAAAEAAQAEAAIACAAFAAAAAgD///7/+v////7/+/8CAAIAAAAHAAYACQAGAAUACgADAAUACwAKAAcACQAGAAYABgAGAAcAAgABAAIAAgAAAAMABQAFAAIAAAD9//7/+v/9//7//f8GAAEA//8BAPr//v8CAP//AAD//////P/7//v//v/+////BwACAPr/+P/6//T/7//1//H/9P/0//f/9////wMAAAABAP//AgD8//r/9//4//X/9v/3//b/+//+/wAA/v/5//r/+f/4//f/+P8AAAAAAwABAPf//v8AAP7//f/1//r////5//r//P/5//r/+f/7//z/AAAEAAAABwAIAAQAAwAIAAYAAgAAAAQAAwADAAkAAQD///3/AQADAAMABAALAAYABQAHAAkACgAJAA0ABQACAAYABwAEAAIAAwAGAP7//f/+//r/+v/+////AgADAAcACwALAA0AEQAOAA8AFAAZABIAEgATAAwADQAFAAMA+v/7//3//P/6//3/AwACAAYABAAGAAgABwAMAAkABgAKAAYABgACAPv/9f/1//H/6f/q/+z/7//s/+3/9v/y//j//v/6//z//v/+//3/+//4//b/8P/p/+3/6f/o/+f/5//t/+r/+P/9//7/AAACAAIAAwAEAAQAAgD///7/9f/y//H/8f/s//D/8P/u//v/+P8BAAcACQAKAAsAEgAOAAwACgACAP3//P/+/////P////j/9f/4//7/AQAGAAYACgAQABgAGAAQAA4ACgAKAAoABgAIAAkABwAGAAAAAQAKAAoACQAOAA0ADgAFAAsADQANAAMABAAFAAYA/P8AAAcABAAAAAAABgAGAAIAAgAIAP7/AQD+/wQA/f/2//3//f/y//P/9v/6//f/8v/2//v/9P/5/wIABwAEAP7/AAAAAPz/+v/3//f/9//+//////8AAP7/BAAGAAUACwANAAsACgAPAAsABAAIAAUA//8CAAIABAACAAMAAQABAAMAAgAHAAUAAgADAP//AAD//wIAAwADAP7//v8EAAIA//8BAAAA/f////7/AQD+//b/+P/2//T/8f/z//H/8v/4//r//P/+/wUACgAIAAUABgD///v/+f/1//n/+v/7//r///8CAAIAAAACAAIAAAAFAP7/+P/+//3/9v/3//3/+P/5//v/+f/4//X/8//0//j/9f/5/wEAAAACAP7//f/7//T/8v/r//D/9v/2//X/9/8JABQAGwATABQAFwAXABoADQAIAAgABQAEAPz/+P/u/9//5f/y//b/6f/i/+3/8v/u/+7/7f/2/wEA/f/s/+T/8/8CAAMA/P8AAA8AIAAjAB8AGAAYAAsA+v/4//v////2//b/6f/2/wYABgD7//T/+P/s/+n/DABHAGcAZABHAB0A/v8VADEA3v/Z/s791v3O/t7/5/8O/0P+3P3O/Rv+C/+6//X+bv0O/nIBCgTjArH/6P4BAdkCHAKWAF8AAgF2AML/mQHSBCAF4ABj/fz+tAO1BXsDvQBwAEoCogP2A9gCwQAC/zj+Q/4S/sL9ff3N/Nf6tPmW+w3/NQAr/fb55vqQ/poApv++/qL/MAAG/3/+pgC0ApwBoP70/f//mwG/AbIB6AEUAWgAdgK3BjEIGwU5AosEdgkoCqAG2QQQB0gHfgPoAHoDlQV3AbP7z/qk/Jn52vKB7zvxRfL/75juz+/W79LscezH8d72S/X08qb5VwZNDBwJ9QhrEbYZShkAFtsXShsWGcsS/A/aDyAMogPt/E77v/oC92LyXPBa8B7v6e2y8Kr2RPoY+iX7Df+0AesA4//gAN4Bqv8v/ZT9ff/N/o/7ivog/ET9Xf7UAWAENwRsBAYJEA6/DmcMUwuHDIQMUwpvB28HMgegA8T9LPsb/FT7F/dB9MD2sPkV+cr1P/XV9lD2wvSK9Xz4PPn19gj1OvaH93b3Bfc5+Bz6EPyd/cj/KwEXAUsB3AEhA+kDBgQYA30BWP81/UX7Dfq8+XP5nPlE+oP7+fsc/I787Px7/VT+0v8uAXYC5wIRAzUCCAEsAMz/0f+LAAwC0wMbBb8FzgW9BIkDjQMZBNwEowUuBgEGdgUUBV0E4QJOAfwAMAGwAqQE1QWOBd4EeAS5BMYF/wYGCDII5ggDCpIKmgomCoEJVwnlCeQK3Az7Dj8QjhANEEYQdBFmFIIYJxwNHr8fQiEYImQh/x0zFvYLBAVLBccHWAUj++LqM9iaxsG5/LKirqGmfJy8muWkFq7yqHScgpworXa/ncxF3fD1WAmsDykU2SSLOfpAvjqDNjw9lUdrS/RG5j2bM6cqCiN1HYcYJRJNCekAW/zu/LD+B/xA85zpXeYF67bxovQR84zwe+7K7Jzs6O+Z88X1+va8+W39ogFdBesHZgczBz4LpRF0FKQTVxKhECcM5gUuAiEBLP8I+/r2xvQ78uTtZevg7VLzhvbH9hn7LAZrEDwTwhMhGM8cUhxEGykg0SbfJ0YjPx1qFyESgg4kDNwIZwUtBd8FGwVVA+QFlAzUEp0VGRnIH4YlySZfJRgnIisoLX8skCz6LosuziUhFYQCavNW6lfmE+Qp3xPT5b30owOOCYEAgACAAIAAgAeLzJ3Jqr2wkbOWu7DLVd/W9tYNQSSgNm5DGEviUGRVC1TfSmxAujyqPnM9zjPTJNoUgAbP+CvttOV541Ljt+Pl5VfrL/A18UTwfvCl8wH6GgOeC3sRKBTpFJQTOhLwERcSrxJnE70T3xFxDewIvARdAJD8ofrh+SP5Dvj79sT1mfPE8e/xrPS++E39/AHqBYoIfwmQCpYL7AvBC84LXAyADHILEgncA7L7lvNf7oHrgurl623vZvKG8nnvY+u/6szuJfWK+jz/ZgNeBvAIPg/ZFsoZTRctFeAVmBV1FDYTmBCOCewApvrI94f1d/K37gXq9uZs6ODtYfNF+E/+dAYQD+wW2B6aJg4tOTF7NJI4NT6OQmRBLznhLJgfzRJEBhv8BfS26v7cH8vcuW+rf6C+mMuT15L/meCo27gQxFPN+dkN5+fxZf7mEQQn3zZ9QC9HAUpNRj48Wi55HywRswWT/Hf1wu6r6Mfhltoe1T3TbtQ92jjlqfRpBVIVlSN1LaIyZTR9Njo58zrcOR03PDIwKeAbAQw9/nXwXeQ+2hrUwdAqz8bOfM8j0ljWvt115jXwqflNAysMmBM8GWIdfSHcI5MkKyIiHsIZuxQvDzEJFQOj+3DzKOy56HjnUeZZ5d/kmOUQ6M7rzvDk9aj7JwFWBf4IvAyFD4cPtg/jEQ8UvBENDMQGLAK+/Cn4Hfej9+j2bfT88mPyLvNT9Wj4PPxKAUQIrg8jFuQaSR49IOQhwiPIJkgqhCwMLJco+SLIHDUX4xEBC5YDEPyO9VzwTu3F6z/nYN9D1ubNWcf+wqDBmsE7wDG/w8Jtzpre6us58yz67gUoE0YcQCKMKncxWjETKiIjcR2zEor+8OTOzqC/vbaXsSGxc7WfvprJWdYU5an2kgg9GSEqMjzeTiJf22rlbrFrImLTVExFbzSgI90S4AFr8CTg99Hxxca8grcwtpm4gb9Py8/Z+eiM92wFTBFaG18jBSkyLJ4s0Cr9JdcewBVkCw3/lfK+5wzefNSIzbTLkM3c0AbXp+Af6yr0xPwhBsAO8xVRHNMiGCk+LlcxdzCCKgggIRSPCIH9D/OS6qvj4d0O28nbLN2X3IXcfN845RXs8/XcAQwMbhIwFi8ZthpgGykagBYZEQsNkAzkDaoNkAsaCqkJywkwC7oPVhVlGR0cRx9tI2Un0ykHKUEjiBrDESwKwwNg/db17usj4PDTXskBwUq8H7qxuKO5HcLS0o3jS+519e3+XgieDH8NmBCPFQsVOQ3XAxv+qfez6m/YIsebu0G1LLU6u0rH8tbs5x/5Xgp+GyArRznIRUBR7FptYfdjHGEFWPdIjzZlIsYNPvqm6l7fWdcG0l/P18560CzWr9+36gf2xwL0EHEetCmqMVY1ozOsLTQkIxjUCNL30ee02VzNpMKsuzO567jsuQu9mMQ00QbhL/GoAdgUpieVNao8E0DpQEA+MDhhMEkotB/qFYEKeP8b9kzsWeHR2MzW5dp/4D3m7uwk9hMBgQraENYUeBiNGsMZWRaVE2sQ+ggR/cPxAes058TjZeHY4T7lP+v38gD7ogJuChMT+hvXI3grczK3NmI2zTKyLy4vei77KIQfTBaPECMMoAU6/KLxfObf2anM4MK2v6y+Krzeu3XEY9O+3o7klOon82L5nfyUALUHfQzwCi4EEPys85joP9pSyuO8hrW/tQ+8LcY+1H/n0P10ExYnUjn4SW9WCl9TZYtpfWmxYq9Ue0GcK5YVAADk6p7YmctWxQbF08lO0rjcfeg09vMEmhNMIUct+DXYOVU5ozRnLHMgeRBX/aLoLdWTxJO43bF4sFSzS7qbxP/Qad/G7+QAeRDBHRIplDIyOmE+mjxdND8oQBolC+D77O9k6OviLN5e3MrfuOXZ6A/pT+uJ8w7/fghXDzYWyB7tJNckzB+FGlsVOw1KAg/5V/U09IbxIOyH6NXpVO127//wMvVZ/TMHvA97FmUcjSEmI9ogRh6PHhEgHiCpHhkeaR+2IfEhFx7ZF/UScQ8CC/kEFv9I+ePwm+V52SrQ4chowka9rb0gx6rWZOSg7Nn0xv9jCAYJbQYwBTAEWP59897nTt3C0Z3BL7BYo/KfCKTgrAK5fMsV5TMCPR6oNm9MK173abNuVW4gaiFim1VYRVczcSAIDpD70+mT2qTQXM1+0CXYm+P38RkCLhLTHv8mfyuiLR4s3SXQHI4SDQdX+R/qodpXzD3BT7kBtNGycLjExJbUH+Uy9gwHzRVLIckp3S95MrwwmCtcJSceohVJC1kAivXu6sXiLd8I4bLlJOva8eT76gfYEa8WPhhTGggcWBk+ErQMwwq9B/n/eve/8a/s0OVb3jfaE9pM3dDhWOcI7zD5PAOPCScN0RA3FcMYURvRHdofkSBpIKgfBR5QHAIciB3eHosfPSF+JBEnHybaIVscUhdZEsULkQMD+ynydOf826XT289XzeHJDcrW0b3dIeXZ5s/pFfEh9471ge8b6/7pSuVJ27HQ+8oNyKvB/LjTtMy6PsaK0Vzcae1JBrQgzDbVRx1XYmPZaQBoUmCiVdVJ5jtaK74a2QwqAjn4k+5t51Hl1ebS6TDvtfjGBYsShRxnI5gm4CVOIfkYRw0JALjzBOlj3tnUGs7WyT/Ga8MYxCzJztG13BXpLvZpA6QPuRjBHeofNSBXHXwXUBEtDCgHOQFz+0/3LvVz9Vf3qvmr/H4CogryEfsWExzPIF0hnBxLFhcQjQfQ/Pny2ux96UHnluVs5I7k4OSf5HrkFOZt6VnsNvAz9qD91wMOCB4LgwyADA4MpA0sEVcUYBYnGZYeuiMiJlknzSmCLO8tai8FMsg08DWTM10sVSK0GTcT9QupAlL5NO9b4zrX5c2xx0/C1rwbuDC5DMKPzDHQC9Bh1XHfkePp31DefeLQ5EnfbdeW1LTWNNa5zyTJ4MnJ0QPameIW8OgE9hvFMEdDglNEYEdnp2itZK1cIlKrR3Y8eS+DIi8XrA2+Awj5C/D/6ubqr+0f8kP5VQPoDKwS3hSwFUsUrA4JBfb5YfB76MngF9hpz5vIJcTtwFS/TcEUyLjRc9y96Pz2sgSBD3cXGh2MH94e2xwNG6cZUhhqFnQTARC1Da8MEQzqCysNQg+5ESIVTxhKGbYXahQyDtMEAftc8rnp4+Ga3encgN2F3n7gZOET4CDfh+Ch4+7mOOsu8bv3qf3bAi0GPQheCvgLqQyNDkgUrxtEIYckcigrLawvIjC0MTw1Sjj2OYQ7uT2WPvo7wDSjKe8dLRRmC1IBmfav7FHiotWUyHC+CLdGsN2p7qeYrn67BMcgznbVlODX6fvp6+Qc4uThe90+1KzMy8q+yz3JKsRpwiLHH9A62pTncPwaGHY0ykwQYNtv+XmHfPl3SW0dX5RPG0BzMFAhCRW/C/ECQPmZ8HPrBuoX6+3t/fKQ+n8DCAsiD0sQFRA7DVgFQPqx77XmLt7a1VbPAcuWyJrHZ8cPyELLWNLU2+jlEPHn/WIKLhRVG2YgqSJkIjog+hw/GkwYfBcZF/4W6RbWFdUTORJ7Eb8QAw8ODUsMwwxwDEkIWQH7+dTyOeu54+zer9yA3MTdYeDT5DzpIOzy64Tq7uph7XzwyPO89x78uwBcBVAJPgwxDsEOYg5MD/0SOBguHVUhHyXqJ9Up7yvxLagvvjCYMVQzJDUGNmk0aS+xJ/Ud5xNNCqQAjPbr62ThTNdEzavD9rqts5eu4qx+sNC5zcX4z3DYUOLE7A3zPPLa7DvnnOLx3EbWwdHh0JnRoNEA0uTVwN5v6mb3dQbxGa8xi0lkXR9rH3Rfdxl0MmqlWi1ImzQVIj0RBQMr+KLwfOtf5yfl9+VZ6jbxePjl/4EHcg9IFssZxxi4EywLpv8P8mvjENXLyLi/9Ln/thS3DrsFwqvKNdXi4R3wuP4IDfkZVCQ0LFoxNzMkMd0rmiSCHAkVkA5dCRQGIQV1BYkFeQXSBgYKWw3UDv0O1A8GEjsTkhAUCjcCgPox8irpiOEE3b3ab9kQ2q3dr+IH59Lp2ev87YbwF/Sg+Bv9EgH+BJMJ5w10EPoPGw6FDVkP9xE5FCEXkhsyIEMjASZ8KRgtcy7NLCMrqSt/Lekt0iqbJPMcGBWZDOUCo/in7vTkfdwM1rrQJ8t7xYPAO7w9umq9LMURzoDVvtzx5X3vxvSA8yHucejn44neZ9nI1unXf9o/3IreeOMa643z+fz0CJYYpSspQGdS+l9eaLxrZGoDY5xVnENcMM4efg/hAoH55/Pt8J3vu+9n8bP0rfiG/AEAbwN4Bw8LlAy5CmwEcvqQ7mTh/dLOxL656bKfrz6wdrX/vvnKu9fA5I/y+QAmD5wbkiXfLKYxUTO5Mdgtyye3H4QWDw6PB2gDkQHsAUoEwwcRDN0QShXfGPcbxh0uHSAboxjnFF4NxQFV9fnpKeB617nQWswYyxDOhNTV2zDiZ+fD62vvhPJB9db3wPrG/ZoAOwSkCCIN6Q9CEKsP4A8dEiIVrBfbGYIc+x8AJJwnByosK4kruivHK+wrlSwYLZsrOCeZIPsY/hDpByX+7fQy7Sfn9eEJ3FfVrs1/xW69Ebfds1q0A7rbxC3Rl9sT5YPvMfgT+uL0/uzy5lPj6d/m2zXZn9oD3nvgI+MI6VTywfwICJgWGSnMPVlRkF8HZ1hpQGiNYh5WdUNVLWEYKQgW/EHy3ero5x3pc+zK8Db2xfvOANQE3Ad1CokMyAzDCLAA9fVM6bPbPc6uwRG2sq3sqzCwYbgIxJLSbuIT8kUBRQ+XGssiXSdPKLAmdyS/ISwdsRYmECYLOQjpBnoGxAa0CHwNxhSLHfQlHy2KMZkxXy1hJjwegBTMB034aemi3rrXxdHCy1vIf8mUztrVM91v4xnp4+7O9FT5bfuJ+4X6Lvn09/b38/m9/Of+AAHMA/0HHg0dEgcVcxYRGQQeYiP8JjApFyucLKYttS7ALs4s7yjeI8UeKBvGGWYZfBetE+UOfgkjA237WfMV7OPlPeBs2iLVn9BUyxvE9Luptqy1CbmDwIjKl9S73ZjnMPLS+TT7yPdd8z3xdfFB8snyfvSL+Bn8K/1R/X3+FACQAc8ExgylGpYsoz1ISs1SCFmTXJ1a+VC/QHkueB6PEdIFJvti873ubOuU6MfmGOZc5svmBecp6HPru/Ci9FD0EfBz6rrkDd5A1jbOLchAxlvIFc0O1H3dO+jl8Qv6AgJHCvER9hfAG+UdJiDtIpQkhSPSIBkeHRwLG5canBmHGM4YNhrsG6Qdmx8uIZEgthw7FgAPlwfm/mT0jumo4N3ZnNVw1PjUhtXH1hrahN+J5RDrG++R8QL0HPdk+aL6TPty+tz2OvKU8ETyDfWo95/6pP+WB+URRRtFIdMk/Sd/K78u4jBPMeEvmi0iK98nBiSmH9wZLxIBCwUHcwYdCNkKaw0hD1kQCBBUDB4Fofyf9LDthefH4YzbH9Uqzx3I+r6ZtZGvdK6dshO87Mnc2f3qA/2DDg0ctCEDH3oXcw9pB939N/NY6i7lcuLD4E3haOX666LzD/05C+oerjTMR7lVYl8sZhBoxWGXUt48HySSC172++TH1q7MdMj/yWbPxdcP4ifsdfQG+9IARgamCgwMoQibAcv5m/FJ56fa/M3Owzm9tro6vdvEGNBg3fnryvtgDF4cnykZMtU1UDbtNHUxKysaIooXhg0bBhkCqwCvAJwCWweADjYXaiARKTEvMzGrLuAosyHTGZMPxwE38pPjJNc5zS3GfMK3wqnGpc3H1wflcfJe+6H+aP8jAOv/XP1Y+PHxXewN6rLqc+y/7ufxavUC+rsBGAyeFuAfmidZLRExpTN1MygueCSMGQUQLglUBacCyv+l/kUBAQfUDcYTiRcxGX0aMBxAHT0dPhxUGaATTwwRBLP5Cu5/5Anfrdwp3Ird9t/W4ari7OBv243UzM8jz7rSw9mU4gzrO/XwAtkPHxXFEXgLzQVpAM75XvKg7GnqIOrT6D7nU+mE7gfz+/Z2/kMMRx7lL2s9Z0ZwTSZTt1MsTPc8XSl1FPsAuvCq493ZrNRk1GXXndwZ5J3sgfOK96j53/tj/28CAgIg/b32bvGd7GHmRd4i1qrQ9s5y0LTUUdzS5uLx2fuIBeAPhxmLH8ogzh5hHBsbbxpzGeEXkxaOFtYXLBkhGQAYLBeMF9QYoBpAHXkgziKIIvQeARlpEt4KKgHS9A/oJd1x1IfOGsyYzRHSSdjo3w/o4u8V9k75tvlC+BH2hfOI8JHtIOvs6bXq6+1u8mn29vmO/o0EygqfD88SNRVTF0AZYRptGlwa6RqYGzUbbhkjFw8UBg/CCBoDrP8t/uz93v4qAXoFuwoMD/0QHhH1EHwQcg6ACkwGOAOuATUCMgVICRwMlwvCB50CJ/7e+ln3zvJg7ufqu+c15AngnNrY05bOL9CB2mLpwfaoAJEKohZqIYokQR40Ew0Ihf2N8p3oO+LR3i3baNan08TVbtpD3pPh3ejT9+AM0iIzNeBCk008VbpXnlJvRQEyMxrwAPPoe9Rzxbe8Tbo3vZbFi9Pp5OL13gMyD2sZziKDKesqBibIHBgRcwM49I3kI9Yzyv/BeL6av5/FFtB23U7s6fvnCxsbyifdMII1Qzb9M6EvmSnBIfEY8A9oBxMAIfta+dX53PvI//MGVBEBHeYmNy3mLyAwHi6KKIUedhAZALrvheHW1vHPUMzOy6vOW9W63gXpmPIC+qb+jQBhACz/3vxk+Vv1PvHt7XzrsOn/5+rmHec/6XftMvPH+TcA2AWmClUOcxBgEZgRPBGFD4UMgQkBB3QEmgET/6j+0wD3A10HlAtNERoXuxrDG0wbVxpMGGYUiQ//CusHPQZlBScFUwa/Cb4OaBT8GociQSkBLI0olSAbF/UOUgg9AoD89vYZ8cTp6eHC2cXPpcPqusa87siU1zrjMe7L/HMNZBjIGNsQ/gV1+Z/pn9hUzCrGMsEru7i3qLu+xdfQwdmO49zz1wsJJjg8F03KWclieGa6YoBW1EKLKlIQzPap4dPTzsy7ylfNgdUi5O727wgyFcIbaCAHJQAntCPxG+8QbgN59MzkwNWyyIy+Yrb/sHuxGrmaxTLUjeSu9gEKpRz8K5Q14TjgN+gzRy1pJK4bWRRxDm8KTQgoCY4NaxTCGiYfeCO7KTExoDbGNxM1tTBxKzwlqxzpEEwBWe+j3ePN4sEsuhC3sLjRv9rL/9n35qzxJfl2/CD72va78AXpneBC2IzRLM6UznjRVNXI2r7iguzD9v0AZQr7EaAXOByMIOkkISkeLEstqixIKr0lLB+5F6kQvQsaCiAL2Q0XEkIYPR+xJAooFCk5KJAlTiGyGxoV7w6mCVIEWv8N/CD7mvu9/Jb+4AAYA1cDGQCx+VvzjvCy8KbxvvLU86vz6e/M6N3ffNXvydnABsBWyZ3XmORW7yP9eA82H68kJiCmGBoROgdq+rHuFOdu4TDbENVI0wHXztz44DXlRO90AUgY1C2uPh1LZlW+XQtg0VeORKwqXQ6X8WHWRb86r0inNadvrtC9S9Qm7R0C2RCEHDsnzS5ZLw8oVRy+EKQG8vtT76PhP9URy4TDpr9qwALGMNDK3svxogh6IcM3EEefTsdQCE+ZSHo85isfGv4KTAC9+HTzKPEd80H4zv5dBm0P6RnsIw8qAit+KL0kFx9fFQYHE/bo5IjUlMXlub+zR7Qiu3HGxNSc5LPznv8yB38KCgpjBlQAyPfu7JLiptvI2NTY3NoD3/3lXvDq/AoJpBM+HYUl9ir1LN8ruyizJAAhhh3VGe0W2hTFEbUMoQcHBQEFmQY4CFgK1w5OFq4epiQ1J44mHyPaHdkWCQ7QA+/5tvGq6//oGetK8VL5CAHNB2UN5RCvEC4MdwbVAsQBBgGh/oz6PvVs7sblf9ud0K3IxsepzqXY9eBU6XH35goCHAkj3SApHE8XKg/aAOTvveFh1kHLWsESvdu/PMYDzf/Vn+VM/aMYkjDLQR9OYVgYYMlgOlYwQYYnBw7p9NXbtsWOtlaviK7Xs3jA3tRf7RIDqROrIcgvNDs/Pi03gSlxGpsMVv+Y73rdXs3+wt29uLscvAzAjMh31e3lH/nfDtMkiDaSQV9Hl0rRSqtFEjpTKnkakw2uA6D6lPKj7l7wRfZT/ugHxRKOHPoiASX6I7Qhch5bGNEOKgRe+Xnto+Dv1RHPzcpfyFHI5soJ0HXXfd+A5obswPFw9Yn3WPiZ9jfy++197BHttu1P7hHw3PMi+vYBtgmhEI4WmxpNHM8caR3zHWoeQh9mIIohsiJlI5Ei+h9aHOAY/RUOFA8SfQ9CDTsNrA+vEsgUnBVuFe8UrRQHFC4SPA/yC7sIggVEAp3+DvrA9azylvDx7irt/eq755LjnN++3Nja39kX2wfgfOiK8M70/PZs+7gBVQTm/0v4lvMa8sjvZurl5IPicOIp4nbhmOJD5vfq1O8K9g7/KwrPFJEcbiELJrgsxzRLOvg5wTRXLQ8lNhoHC8n4ZecU2nbRvczWy9jOO9XE3UHoA/V2AwoR1hlcHAsbxxi+FXEPZwQy9iDpHeBH2uTU8M7iyr3Kp8671eTeVupt+III7RikKKI3wkQjTbROfkp8Qzs72zCWInIRYQHY9XnvqOwW7ZbxePrCBfoQFBujI0opbiqoJhUeZRGdAa/wT+At0nrHs8DHvbe94r+tw+rIGtBG2H3fPeXk6q3w6vXv+cn8Zv7z/XL7/fYY8vHuLO5v78rxCfZc/FYEQQ0vFo8e5ibDL343ODxgPeE71De/Me0qKiQkHfsVrw9qCtUG5AW1BssHgAl1DCQQpBOtFtoXIRafEokPcg17C5EJagcQBe8CVwEvAPH9ZPoO9rXx9+6K7nbvFPCJ8FLxBfE+7uPow+IB3dvYbteg2eveV+Vx6+3wsfYA/VoB/wFOAK/+6Pz9+LnySOtp5DHftts/2V/X5dYS2WjeF+f98vYAHw/YHAYq7zXwPx1HZUkKRQ47cy6YIPYQa/+Y7TDejtNzzerK68to0UXbs+fB9ZwFnxWEIuAp+isHKgoktxlYC7/6gOv931HYX9MV0L7OddDY1SLeX+dD8J35ZQTqDzcbIiZuMBM4VDvoOl04ljOaK5YgyxOEB2T9Sfbs8fvwIfRq+jQCxwrsEzkb8h6jH7kd1Rd+DeD/yfDW4VXVt8xAxyPFxcZGy3nREtnK4fvpxfAo9qb5Avvy+l35ZfXs79nqQedv5bXlIeg37CvyYvlmAAQHIw4yFXIaZR44I9Eoci0gMOIwri8ZLdgpfSW1H7YZLRQpD/cKcgipByAIjQnnC30PIhTmGPEc7x5DHlsbDxf6ESEMDAYJAa79Jfu++HX3QfjF+lv+UwJFBpkJbAvdC9sLvQuMCuYG6QAt+VfvmeOz19HNpca8wYLAMsUJzmDWU9y44+fvXv00BQkGEgV9Bu4HjwQb/JDyiOoK4hvXjsuKw3/AL8HHxU/QtOHI96AOtSPlNblFpVMlXeZdBlSeQ9Qy7yJ5ELr6a+ZO2EHR4M6nz6HUQd5h6k/2EALUDjAb+SKqJKYihx/qGxwWNg2WAb/1G+yP5KndMdZXz0TLa8sZzyPVcd4D7BP83AoZGCElqjFEOsw7HjfoLxspLyLKGM8N9AQpAGn+Nf3P/F/+7gGkBYUHSggDCkoNPA/lDa8JdAQg/1P5uvJJ7E/oOeaz41Xgdd1h3KrcB97X3y7hV+Ll4yjmAOha6ZTqJOzd7ZHvGfH88tb18/lS/kgCbQaVCt0NARBIEWsS9ROOFbgW4BfwGY4cFx8UIfQiiiRRJTkl4CNvII8bZheQE70P9Qs5CYgIUgniClEMKw0jDlAPARBdDyIN7glbBen/+/qI97v1lPXJ9n/5o/2JAhMHKAosC9wKmwmrB+EE/ACu/Cf5cPYm9BLymfBX8D3xpvJO9Ej2kfjC+l/8ff0Y/o39J/sJ9zvya+1F6Frjnt+o3VDd5N1+30zixOXN6R3uDvMV+LX7zfzM++v5s/dL9XLyaO+c7KLq6emV6rLsSPCF9dP7WAJBCDsNyRFNFhkaShzWHCUcDRoBFkIQvAlGA3L91/gQ9ir1Rvas+fT+KAUvC5wQlBXQGV4cxByNG0sZwhVtEOUJywMg/1/7lPeq8+Lw8O958LbxfvMn9sP5If5qAgcGrAgmCscK9AqECuEIugVcAYn8z/cK81nuq+pr6JrnQOhj6vbt8vKo+B/+LgOjB9QKLQw5DMgL0Ap3CVgIXAcOBoIEUQM7AvAAsv99/iX9gfwS/Wn+IQCvAgsGOAniC4wOxxDyEfoRvRDYDe0JRgZdA/wAff/O/vH+vwBkBGUImAtPDvsQZBNqFfQWgRcVF3oWNhZbFgkXIBgPGZcYCxaHEUgM4weHBPcAWvyf9/nyke2k5sDf1Nnt1EzRdtCV06XXTtkx2THcUOQn7XHx4fH085D4Sfqz9nfxu+3k6Vbkut5P2/TZqtqD3obmzfHn/rEMORr9JtExkDqEQYZGlkfGQsY5iy9AJUYalg4TA4z4dfC+6rjmGOTD4uPibuWM6/zzj/uWATkHzgxgEFIRmg+/CqMDA/ud8RnoFODX2VLVQNKz0ZHUctpT4uvp8e939lP/WQmgEn8anCC6JEwnVylaKs4oGSU4IIYaDBSlDZoISAUEA+IAiv4N/TH9w/6IAIoBPAGq/+T9RPzv+rf56vdP9RDy6O7164Lprecv57Hn1+cD5+PlkOVW5UjkvuKg4fDhnOOI5lvqH+8w9YL8DAS5CsQP7hJ6FBMVyxSwE0ES6RCaDxIOXAzxChcKJArQCvEKLQrdCRwLGg3kDqkQuhIbFfIX3Rp5HJobjxhkFLIPhgraBK/+d/g2857vue1G7d7tHe9K8Yr0fPjN/DsBDAWJB9oIWgkjCXQIpwc2BrsD6QCd/rj8MPup+kj7V/zF/ToAwANzByEL2w4dEjQU4RQvFBMSrg5HCkcFhgCZ/HH5OfdP9o/2kfcU+QH7Af1C/if+VPx++a32CvQu8X7u0+wd7JDrTOvt64Ptae8W8ZXy//OV9Qr3gvh5+i/90P/JAXID1AQdBVIETwNrAiYBZv/d/dz8y/wQ/rsAHASXB/IK+Q2KEMESRBQ4FHISqQ90DNcI9wRYASr+Ovuo+P/2TfZX9pP24PZT99H3Hvhw+Nr4mPgj9zP1/PNI8znyxvBb71DuX+3B7IPssOwi7cDttu7975jxmPNR9t35tf1WAX4E+gaOCOcINAgSByEGaQWLBJMDJgP7Ax0GNAn4DOgQZxQZF9MYThmPGKcWIxQFEU4NVAmlBfkCagFXAI3/cP8PAMkAWgHQAWwCJgORA8oD4gPcA7IDVAPPApsC0QI8A/wDQAXBBgIILwl9CvwLZQ2uDg8QqBErE0kU9BRMFbwV1hWNFQ4VUxRlEzISABGWD7MNkQttCWEHVAUmA6IAaP0J+fPzlO466fjjxd612TvVotHczn7MXsogydXI7ch2yRDLnc010JvSydXp2V3ec+Lr5cjohOtp7vLxKPbd+pP/6wN0CKENAhOpF6cbgB+fIuIkvSZkKHEpCyquKhkrRytvK0Ur+Cm3Jz8lniLGHx4dpBrbFw8VuxK+EEMO7wpDB3kDzv9M/AL58PU785nw5O3E63jqdOk86DTnyeZ25n/mf+cX6cDqjOx67iPwePHb8gP0fPTW9GL15PV69tv3OPr3/Mr/twJABfsGSgh0CUcKOwo3CUsH5gTsAroBRAFcAb4B1QGfAZ4BAQI+AiIC9AHYAagBUgG7AMP/k/5Z/fT7afrA+MH25vNT8NvsHuow6NzmFOYQ5gXnIela7F3wm/S1+JL8IAASAxwFLAaQBi0GMAXxA98CMwLjAfMBbQKHA2UF3gfZCgwODxG4E00WrBiSGtAbgRypHCkc6xrnGHoWyxMhEZ8OfQzEClcJSgiQB/gGcwYJBq0FQAWuBAEEJgMMAsAAKv9M/VX7bfmM97D1APSA8n/xV/H18dDyuvPB9LT1Xvb/9rj3HvjU9xr3Zfb99Qb2YPbn9rz3HPnK+kn8ZP0d/l/+Mv4I/gX+pf29/KP72/qN+sX6mPvm/Eb+V/88ACcBJALVAu0CaAJlASIAsv49/Qf8F/tv+kf6BPtJ/Ir9h/50/0IAlQBoAN//Bv/s/bn8dPty+i/6mfp4+/L82f6fAO8BwwJHA4sDuwPcA78DZgP/AqsCTQJHAp8CEAOEAx0EsATOBIYETAQqBPADwwPBA8YD2QPxAyAEZASxBLgESQSUA/MCegIIAqUBWAHxAGoAKABKAIcAawDt/yr//f1A/Fz67fjq90H3+fYH92/3Bfiz+Hb5Xfo1+7/7CvxN/Jv8y/zy/Bv9J/0Z/Rb9P/2N/Q/+nP4V/8f/EQHwAuMExQaVCCYKLQuVC7YLmAsRC/gJYAh3BoMEqgIrAQUAGf9f/s79tP0D/kb+Tf6C/jT/sP/B/wkAuQAQAdAA5wB2AV4BaAB+/57+fv2R/FH8LPxM/Gz9Rf9FAcsDpwbdCDAKOgvVC2kLqwoFCsoIWgemBp8GHQbnBYIGAAcjB5AHKQjPB78G1AX5BCgEyAO2Az4DxAKVAlsC7AHMAfIBygGqAeoBwgH2APD/g/7e/Nf7bft6+mX4v/Wq8n3vVu0N7Ofpvebv4wPiqeCT337e9Nyx22/b29vZ3I/eJeCe4H3hqOT+6KXsSe+L8YTznfXY+Ej9vwESBSYHwAgUC1kOCRGrEvgTcRXVFnwYDBtKHd0dtx0lHsse+R4+HkMcABlWFUMS5g/gDdsLigkMBzwFfATcA6cC4wCb/un7dvmV97P1aPPR8JPuAe1W7J3sKe3d7RjvIPGQ81T2TfkE/Dn+XwBlAhMEHAWXBeoFHgZ+BuIGAgckB8EHsAiiCY8KKgsWC+cKFwuFC5oLAQuCCTsHIgX9A5YDCAMMAqcACv/c/Wj9Cf18/LT7lvpE+Vv4/fdu93j2t/Vd9Vj1fvXN9eH1sfWP9bz1dfa699L4Oflc+Qj6/foO/Gb9s/6S/zwATAGJAr4DIQXyBrEIaQpRDBYOPg/+D6AQ0RB7EDUQKRCUD3YOaA2ZDKgLtAozChEK6QnUCc0JjwkACYII1AfLBqEFLAT2AUr/O/2C+6r5Cfg59/L2lfZ19rD2+vZV97f3yfec95P3kPdd90/30PeS+CH5vflQ+nL6I/rM+Z75e/lP+Sb5H/l/+U/6R/sg/AD93f1n/or+ZP79/RX95Puc+pL55Ph9+Cf42fdp98L2Gfbq9S72iPbA9sz2+vaD9yL4o/he+XP6YPv2+/v8jf7B/04ARwHxAhgErASzBdsGOgdtB04ITgn3CeEKygtVDPQMBQ7LDvkOGg/DDqMNaQyuC8gKcAmCCBUIjQcjB0EHRgcIBw0HQwcIB48GMAZvBUAEPANDAvsAnf9d/gv9zvvr+lr66vm/+br5f/mj+Uv6zPoA+3D7Nfy1/N78GP0Z/bL8TPwx/Bz80fto++L6fPpj+oH6h/qQ+qz6hPon+v/5H/ol+gX6uvle+RL5q/hO+CT4/Pei9y33Evce9+P2r/bH9ur20Pbv9lj3yPcz+L34YfnT+UH6/vr/+zT9ov4WAGsBqALVAwQFQwajB/AI9wngCo8L+AtODNoMbA2nDZkNew1DDf8MsgyKDHAMWwxNDEsMKgz4C28LagopCfIHpQYGBWMDogG2/8j9OPwV+xP6Mvmg+ET4E/gG+DH4e/iu+LL4vvgU+Z/5M/qz+jT7oPvV+wn8hfwX/bz9b/4c/wEAIwF/AvQDfQUVB2UIawlcCjkLxAvrC+0LuQtiC/8KpQooCnEJngihB+UGLAZBBUsEewPiAk0CyAE+AaIA4v8E/9H9Zvyo+lD4wPWk817yMPF873TtzeqQ54jkaOIK4QzgE98e3ondt90o3pXeUd9+4LHhKuOC5YLo7eoF7Qbw1fPZ96P7G//7AXYEFwc/CpwN2BCME7QVARjVGr0dIyAVIqwj7SQcJmsnTigsKEUnHyazJF0jBCL/HyId4BnUFu4TWxHbDisMIglIBswDPgFs/lP7G/gR9b7yCfFo7+ftxezV6wzr/OpO64jrhevO64fsYu2h7hDwS/Gp8nn0R/bZ93z5ZPvY/Dj+BwC0AZACJAPdA0kEiQTfBMoE7wMDA44CfwKyAhED9wISAvAAGQCE/yv/O/8y/2n+S/1y/Jz7qvoV+tn5cfne+IT4Pvi092P3S/cK98z26/Yn9z33nPdo+Fj5aPqx+wP97f2p/or/egCMAR0DswTrBfcGHwgoCRIKVQu3DLwNVA7SDhMP6g7JDsMOrQ6ZDq4Ovw7FDtEOrQ47DvEN2g19DegMKwwgC4wJ7weIBg8FZAPTAXMAGf/t/QX9Nfx0++X6Wfq8+U751/gs+J/3Ovey9j32HPYl9gv2GvZg9qX29vaT9074wvg3+cH5F/qH+mP7WvwU/dH9gP64/ur+d/8NAGsAtADiAL0AhgB9AHkARgAwAFsAbwCaABMBWgEdAeMA1QBgAMH/Xv/2/oP+Ov7//Zf9M/3//NL8gvxf/G/8Ffxn+/b6mPoV+sX5xPmq+Yb5lPne+Tr6zvp5+9f7QPzn/MD9e/5a/3EATAHCAUkC+gJ2A+0DnQRhBRAGxQaDBzEIyAhECWEJRwkyCQYJkwj9B54HPAeZBvgFcQWyBMMD7wIcAkEBgQDk/zD/YP6l/ev8MPyd+z371vpf+v/5j/kF+a74kPhs+Jn4Nvnc+Uz6wvpE+7f7HPyY/C39uf1c/g3/v/96AC4BrQHnAR4CVQJvApoCAwNLA3sD0wNHBL4EGgVYBW8FagV7BYYFgwVrBUQFBwXPBMAEpgRsBDAEFgTpA8kDvQNoA9oCigJ0AlMCRAJaAi8CjQHqAIYABQBY/77+Kv6P/Q791vyH/Bb8vvtd+wn7BftM+2H7RftX+3D7cftv+677u/uF+3P7ivuU+4T7mvvH+/j7SPys/B39if33/Vz+uP42/9D/bQDiAFIByQEnAmkCsgIIA0oDcwOYA6QDhgNkA0oDJQP1AsECiAIOAqMBfwFhAT0BMAFSAVkBRgFiAZoB7AFGAqQC6wITAzcDXQNgA0sDNwMNA9AC0QLrAt0CvQKRAlUC3AFdAfwAtgBFAN7/pv9V/+n+ef4R/on9BP2S/A78dfv/+o/6Fvq4+Y35Rvna+J34m/iZ+KD44vgm+UH5evnv+Vv6sfoQ+2P7p/v0+1H8tfwQ/X/96P1R/vb+zf+mAGcBOgLxAnAD0wM4BIUEugTuBB0FPQWCBa4FigUmBcoEdAT6A4wDVAM4AwsD6gLZAtoC2gK/ApwCjAJ2Aj8C6wGCAQUBXACx/z3/yf5f/vr9pv1T/QL9wfyg/IH8Xvxi/H38yPwG/Tz9e/3b/Tn+a/6p/t7+Bf8l/3X/4v9sAA4BsgEhAmcCrQLmAhsDYwOzA/kDGQQ3BDwEJAQvBFMESQQtBAYEswNcAxMD3gKLAhwCoAEZAYwAFgDH/3P/HP/a/qL+bv5F/hX+4f26/ZH9Xf0k/fn8z/yO/Ef8HPwZ/DP8UPxw/I78tPzr/Dn9hP3d/Q7+I/5W/qH+7f4q/3f/v//O/8j/yP/I/6j/bv9U/1z/Zv9z/4L/q//X/wYAUQC0ABsBawGXAa4B3QEXAkQCYAJtAm4CTgIvAhkCAQLOAaEBfQFjAWYBegGCAYMBkAGqAbwB0gHlAdoBnAFOAQQBwwCJAGsAQgALANf/sf+i/7r/+/9FAJIAxQD2ABEBAQHsAM4ApQBvADsAEwDi/63/ff9T/yn//f7e/sD+h/5N/lT+Y/5u/nD+ff5q/jn+Af7l/cL9o/2Z/Yr9gf15/YD9hP2x/Qf+Pf57/s7+Gf9P/4H/v//+/zwAdAC/AOcACQE3AWcBhwGuAdUB3AHfAc0ByAGoAZoBiAFiASsB6gCbAD4A8//I/6T/Zv84/yH/A//r/vH+Cv8r/0v/Wf9j/2z/bP9q/1f/Yv96/47/pv/l/yYAVAB4ALAA/AA3AXQBtQH5AS0CcgLAAgUDKwMyAycDJwMxAzUDEQPYApgCVAIeAv8B5gGyAYEBRgEFAdsAvQCfAGIAKwARAOj/x/+o/3z/QP8C/8z+rP52/jn+Dv7q/c79zv34/SX+NP5F/ln+bv54/nf+W/48/hf+6/25/Zf9if10/WT9c/2U/a79z/0f/mb+mv7S/gz/J/8k/yf/J/8i/wz/+f7y/gz/Lv9h/6n/9P9UAJkA1QASAVABdAGOAasBuQHBAcYBxAG5AagBkQGEAXcBTwE8ASUB/wDFAKMAmAB/AG8AeQCEAHoAbgBtAGEATQBEADsAFQDx/97/y/+v/63/vf/F//D/MwB2ALYAFAFkAYsBqAHTAd8BxAG+AbsBoQGOAZkBlwGAAXgBeAFrAWEBXwFfAVABPwE8ASEBCgH6AOUAxQCSAGAALwDs/6r/dv88/wP/zP6a/nD+Sf4e/uv9qv14/Wj9W/1k/X/9qf3Z/Qj+Uf6H/pr+sP7B/sn+yf7o/hX/N/9L/3v/u//i/xsAZQCaAMEA7wAdAT8BaQGTAacBswHHAcUBrwGYAYUBWAErAQ8B4QClAHYAUwAxAPT/wP+K/1P/Ef/V/qT+cf5L/if+Hf4M/v799/3p/ef97f0F/iH+Pf5n/p3+2/4i/3b/uP/k/wQAMgBHAGoAlwDAAPEAIgFfAY4BvAH1ARICGgIgAi4CFwLvAdABwQGfAYMBgwF7AXEBYQFXAUoBOwEtAQ4B5gDFAKUAZwAsAAIA2/+n/3n/R/8W/+X+tf6S/mz+Uv47/hb+Bv72/ev99/37/Rz+Q/5g/oH+k/6k/q/+tP7H/r7+n/6h/qL+p/63/tP+Cf8x/2f/rf/w/zYAgQC9APcAPgGLAb0B6gEeAkkCZAKGAqECsAKsAq8CnQKCAnkCbgJaAj0CKwIjAhEC/QH8AeIBwgGjAWsBLgH9AL4AbQAaAM3/df8i/+f+pP5i/i3+Dv73/ef92/3M/c/93/3s/QH+Ff4+/l3+b/6j/tD+7v4b/1D/ev+h/+X/HABFAHMArADZAPAACgElAToBUgFfAWkBewGDAYQBfQF2AWMBRgEkAQYB7ADKAKkAgABdADQAAwDQ/5//bv81/wD/yf6F/lD+I/4C/tP9s/2n/Z79nP2Z/aj9uv3E/df9B/4s/k/+cv6c/r/+4v4T/zf/Z/+Q/8T/5P/9/yYAUgB4AKwA0AD1ACEBSgFnAX0BlAGvAbkByQHYAecB3wHPAbcBmQF6AV0BOAEYAfwA4wDMALUAogCLAGwAVQBCADUAIgASAP3/8v/p/+7/9P/t/+f/0f+t/5j/gv9j/1H/N/8m/x//F/8d/xP/Hf8b/xP/GP8O/wn/9v7p/tv+2f7T/tH+z/7T/tj+2/7i/uH+2v7c/tL+0f7V/t3+7v76/hD/NP9e/57/1P8UAFUAigDEAOsADAE7AVQBawF8AYoBmgGiAagBpgG3AbsBuAG4AbcBrAGYAYMBbQFLATUBGQH5ANsAzQC0AJgAiQB0AFMANAAoAAwA6f/E/6b/gf9Q/0P/L/8b/xP/D/8L/xX/I/8l/x3/Lv9B/1j/cv+O/5r/tv/Z/wMALABKAG4AigCgAKwAtwC9ALwAvAC2ALMAswCuAKEAlgB+AGUATgAzABYA9f/i/8v/uf+j/5P/if91/3D/Y/9e/1r/Z/9w/2X/Xf9L/yn/Ff8D/+b+wf6q/qb+pv67/tf+9P4S/yn/Q/9n/37/mP+u/9D/8P8WAEUAVwBsAIMAhACMAIkAkACFAHcAgwCaAMIA4wD7AP4A7QDqAOkA7wAGAUABgwHdATACcAJ7AlgCGwLSAYcBOwH+AMsAjABXABYAvv9o/wn/q/5b/iH+//0C/gn+G/4n/jn+Rf5J/j7+JP4X/gT+Cf4X/jz+d/6a/rv+4v4L/zz/cv+x//v/OAB7AMkABwFJAYQBtgHaAfwBJQI2AjYCLgIcAhgCCgLdAbEBgwFLAQwBxgB+ADYA8f+k/17/Jv/6/r/+f/5N/ij+Ef4B/uz97v3w/QD+Cv4V/iH+PP5R/mr+l/7B/vf+Hv87/17/h//E/wsAUgCQAMYA7QAIAS8BaQGgAekBNgJuApQCpgKlAoYCZAJAAiACHgIjAiwCJAL8AagBTAHyAJ4AVgAdAOP/tv+F/z3/9P6p/lH+DP7a/b/9t/2v/aP9lP2F/Vz9SP09/Uj9af2X/dP9IP5p/qn+3P7//jT/cP+5//3/RwCTANAACgE/AWYBiQG7AeYBBQIaAiMCGgIJAu0B1AG7AZoBdgFgAUYBGgHaAJYARQD4/7b/fP9Q/zn/KP8f/wr/5/62/nD+Ov4f/gv+F/4n/k7+iP60/uT+CP8v/2T/mP/e/yoAYgCaANEA+gAtAW8BnAG2AcYBwwG6AasBngGPAYcBhgF9AXgBWwEnAfMAsQB9AFcAKgAKAPD/s/9//0X/A/+//on+Zf47/iD+Fv4P/hv+IP4i/jP+P/5b/oX+xv4B/zX/Z/+M/77/+/8tAFsAjQC7AO0ACAEfAS8BOwE9AUMBRAFZAWQBcQFwAWABUwEwARAB6ADFALEAlQB1AGIAPgAWAO3/xP+V/3P/Wf85/yP/E/8E/+3+0f61/qv+qf60/sP+1/7j/vr+G/9C/27/lP+1/9j/9v8XADUAQQBSAGkAgACXALMA0wDrAAUBHAEpAS8BMgE3ATEBKwEjARQB/gDVAK8AiwBmAEQAJwAIAPL/0/+o/4D/XP85/xv/C/8A//H+5v7j/uD+4f7d/uL+7/7+/h//Of9d/4H/mv+6/8f/5v/9/x4ANwBTAHAAkgCxAMsA3QDhAPIA9wD8AAQBBQEFAfMA2wDIAMAAqgCRAHYAWgA8ABoA+P/c/8f/tf+r/5b/hv9u/1H/QP8q/yf/H/8R/xv/KP8u/zb/Qv9P/2L/eP+Y/8D/4v8KACcARQBbAG0AfAB5AHwAhwCcAKoAuADJANEA1gDMALwAsQCoAJQAiwB2AGkAXwBAACsABADn/8j/rP+T/4b/eP9s/1P/Qv89/y3/K/8r/yj/LP8u/zz/Wf9x/3//jP+i/63/vf/X//j/HAAyAE0AcQCCAJ8AqACwALwAzQDdAN8A3wDtAOgA2QDPAL4AtQCtAJ4AlwCRAIAAdgBeAEYAIwAKAOn/xf+0/6D/lv98/2H/Sv88/zj/L/80/zv/Pf9I/0f/Tf9V/0f/Rf9J/1f/cf+P/6H/q/+9/8j/0v/b//T/BgAbACcANwBRAFYAXwBdAF8AbAByAH4AhwCOAJcAmACOAIgAeQBsAF4ASwAyAB0ABwD2/9r/xv+8/67/pP+h/6L/p/+j/53/l/+W/5j/mP+a/6T/qP+r/63/qv+r/7v/y//i//X/FwA3AD8ARgBTAFEATABUAFMAZgB2AHgAfQCBAIQAhQCEAIEAiACMAIsAhAB5AGsAWgBQADkAKwAoABoAFwAQAAkABwD+/+7/5P/Z/9L/2v/W/8r/yP/A/73/sv+0/73/tv+0/7P/t/+7/77/w//F/8D/xv/L/9T/2//X/9v/5P/m//D/8P/v/+r/5v/o/+//9/8DAAgACQALAAsAEAAUABAADAASABMADAAOABIAFAAaABMAFAAVABsAJAAiACIAJwAqACcALQAuACgAKAAnACIAJwAkABwAGAAOAAEA/P/r/+j/4v/i/9//3//h/+P/4//e/9j/1v/Y/9X/1P/T/9//5v/k/+D/0f/W/9D/0//W/87/0//d/9b/2P/b/9v/2v/f/+H/7P/8/wkADQAWABwAHgAeABoADgASABoAGAAcACkALQAsACoAMgA4ADUARwBEAEQATwBQAEsARwBAAD0ANgAvADIAMgAtACsAIgAUAA0A/P/2/+//4f/Y/9n/zf/A/7n/uf+w/6v/qv+n/6T/rP+v/67/rf+y/63/qv+k/63/rP+4/8D/xP/L/9P/2P/Y/+f/7v/4/wYAEAAaACkANgA8AEQAPwBMAFMAXABkAGEAZgBjAGAAXgBbAFIARQA5ADcAMwA2ACgAIQAfABkAFwALAAUA/f/3//L/5//e/9v/2//M/8b/vP+3/7P/rP+p/7L/v//D/8j/y//P/8v/x//H/9b/2v/n//P/+v8IABAAEgAUABgAIAAgACwAMgA8AEQAQQA4ADEALgAtACcAKgAxACUAMQAwACAAJwAbAA8ACgAIAAEA8v/v/+T/3//X/9D/yf/K/9X/1v/X/9r/1//W/87/z//S/87/2v/b/9X/2//Y/9b/1//j/+v/9P/y//n//f/+//v//P8CAAUABgAPABsAFgAaABkAEQARABMAGAAUABIAFwAUABUAHgAYABAADgAKAAQAAAAIAAQADwAPAAoABgAAAP//9//2//X/9//9//v/+//4//j/+f/1//T/+P/8//n/+f/5//r//f/9//f//P/6//T/9//5//v////6//3/BQANAAYACgACAP//AwD6//b//v8KAAcACAAFAP7/AQD7//n/9P/5//z/AAAMAAkACQAIAAYABgADAAUABQADAAQA/v/7//j/9f/2/+//8P/3//7////+//7/+//6/wAA+//+//7/AAD2//v/+//+//b/+/8AAAEABwAKAAoADwAJAAgADAAKAAkAEQASAAwADgAIAAEA+f/8//n//f/2////AgAAAPr/+v/5//X/9f/0//P/8//w//P/7f/t/+7/7f/y//T/+/8AAP7/+//6//v/9P/4////BwANABIAFQATAA8ADwANAAwAEAAQABIAEgARABEAFAALABAADQANABcAFAAUABcAEgAMAAcA/v/0//X/8P/w//P/7v/s/+n/7f/u//T/7v/v//H/7//o/+X/5f/n/+P/4f/o/+j/5//u/+7/6P/p/+7/7//w//n//v/+/wUACwALAAkACgANABIAEwAOAA0ACgAIAAsACgALABgAGgAYABUAFQAQAA4AAAD9//j/+//6////BQD+//j/9f/t/+//8f/v//D/9v8AAP//+P/3//v/+v8DAP7/AwAGAAcABgADAAAA/v8AAAgACAANABUAGQATAA0ADAANAAwADQAOAA4ADAAGAAcA+P/0//b/7v/y//T/6//u/+n/6f/o/+v/8f/x//X/9v/y//T/8P/y//H/7P/y//T/8f/z//X/9f/4//f//f/5/wEABgAGAAYABgAFAAQAAQD9//r//f/5//v/AAD//wIABwAIAAcACAAMAAoACAAUAA4ADgAUABUAFAARABIADwAOAA0ADwAMAAsACwAPAAoAAwAKAAsAEQAXAB0AHQAZABwAHAAYABgAFQAWABsAFAAPAA0ABQAJAAwACQANAAwACwAOABEADgAKABAACQAIAAUA/f/4//b/6//q/+T/5f/n/9//6P/k/+T/4v/j/+z/6f/y//X/9//8//7////9//z/9P/r/+n/6P/h/97/3P/d/+D/5v/q//r/9//6/wcAAgANABEADwAOAAwACgABAAUAAAD0//j/8v/u/+3/8P/v/+v/8f/0//b///8BAAYACAAJAAMAAgD5//j/+v/w//D/8P/u//D/8P/x//P/8//1//z/+v/7/wQACwASABIAFQAUABQAEgALAAoABQAJAAYACAAMAAkACAALAAoABwAIABAADQANABEADwARABAADwALAAsACgAGAAIABAD+//r/+P/3/+//+P/x//P/9P/6//z/+P/9//7/AAAGAAUA//////z/+f/9//b//v8CAPf//v/5//v/+f/8//r/9//3//3/BAD7//7//v/6//n/+P/2//n/7//5//T/8P/v/+z/7//y//X/+f/+/wkAAgAIAAoADAAFAAQABQD//////P////3/+P/9//j/+P8DAAIABAAKAAsADAATAA8AEQALAAcABwAEAAEA/f/4//z/+v/x//n/8f/z//j/9v8BAP3/CAAOAAwADgATAAsABwAFAAYABgALAAUA//8FAAQA/f/2//r//v/6//7/BQAGAAYAEQAMAA==\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ],
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        },
        "id": "kJdFL66iXg0H",
        "outputId": "a4a4f02e-cd21-4c0c-891a-5a254020487a"
      },
      "source": [
        "show_melspec(samples[2])\n",
        "Audio(samples[2])"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Showing ./data/one/fb7eb481_nohash_3.wav\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 504x360 with 1 Axes>"
            ]
          },
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            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
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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>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GFcYz3fxA3bR"
      },
      "source": [
        "### 6. Using Inference Scipts\n",
        "\n",
        "There are two inference scripts provided in the repository:\n",
        "- `inference.py`\n",
        "- `window_inference.py`.\n",
        "\n",
        "We'll be using the pretrained model we downloaded earlier to test these inference scripts.\n",
        "\n",
        "**Using `inference.py`:**\n",
        "\n",
        "For simple short clips that are about 1s, such as the audios in the Speech Commands dataset, you can simply use `inference.py` to get predictions. It can be run on a single audio clip, as well as a folder containing several audio clips.\n",
        "\n",
        "Let us first try **inferencing on a single short clip**:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cfPLqCFkBDEA",
        "outputId": "6822b835-4bf2-4b69-e659-eac1074f2306"
      },
      "source": [
        "!python inference.py --conf sample_configs/base_config.yaml \\\n",
        "                     --ckpt kwmlp_pretrained.ckpt \\\n",
        "                     --inp {samples[0]} \\\n",
        "                     --out outputs/single_preds/ \\\n",
        "                     --lmap label_map.json \\\n",
        "                     --device cpu             # you can also use cuda"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "100% 1/1 [00:00<00:00,  4.45it/s]\n",
            "Saved preds to outputs/single_preds/preds.json\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-m9vvCaWBrYv"
      },
      "source": [
        "Let us check the prediction output:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h8jKtBClBiVG",
        "outputId": "9dc18797-c529-410e-a318-8e23b2ff9121"
      },
      "source": [
        "!cat outputs/single_preds/preds.json"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{\"./data/left/5828dfa2_nohash_0.wav\": \"left\"}"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vFPutSbCOVMa"
      },
      "source": [
        "Seems like it's correct!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QyMTRgvzCDCj"
      },
      "source": [
        "Similarly, you can also provide **a folder containing multiple audio wavs** to the `--inp` argument, instead of a single audio path. Let's take the previously seen first 3 audios in testing list and put them in a folder:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jYDc2xQcCVEh",
        "outputId": "c06c14df-fb07-4d44-9dbd-dd29dbc88db4"
      },
      "source": [
        "# Moving multiple audios to a single folder \"samples\"\n",
        "!cat data/testing_list.txt | head -n 3\n",
        "!mkdir -p samples/\n",
        "!cp $(cat data/testing_list.txt | head -n 3) samples/"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "./data/left/5828dfa2_nohash_0.wav\n",
            "./data/down/cfbedff9_nohash_3.wav\n",
            "./data/one/fb7eb481_nohash_3.wav\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wyBKexn0rCSD",
        "outputId": "34221c48-4c61-4095-8123-1f1309a86b5e"
      },
      "source": [
        "# Run inference\n",
        "!python inference.py --conf sample_configs/base_config.yaml \\\n",
        "                     --ckpt kwmlp_pretrained.ckpt \\\n",
        "                     --inp samples/ \\\n",
        "                     --out outputs/folder_preds/ \\\n",
        "                     --lmap label_map.json \\\n",
        "                     --device cpu"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r  0% 0/3 [00:00<?, ?it/s]\r100% 3/3 [00:00<00:00, 74.34it/s]\n",
            "Saved preds to outputs/folder_preds/preds.json\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0vRSpMTUDAIZ"
      },
      "source": [
        "The outputs are in a similar json format."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O9I0wHJVCwtb",
        "outputId": "534dc968-86c8-40bc-92d7-ddd1ab7986b3"
      },
      "source": [
        "!cat outputs/folder_preds/preds.json"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{\"samples/fb7eb481_nohash_3.wav\": \"one\", \"samples/5828dfa2_nohash_0.wav\": \"left\", \"samples/cfbedff9_nohash_3.wav\": \"down\"}"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vj6fEBhdDNRP"
      },
      "source": [
        "*If you are running inference on a large number of clips, you can also use the **--batch_size** argument.* By default, batch size is set to 1 during inference.\n",
        "\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "**Using window_inference.py:**\n",
        "\n",
        "In real life use-case, audios are typically much longer than 1s. To get predictions from long audios, we thus need to run multiple inferences on various \"chunks\" or \"windows\" in that audio clip.\n",
        "\n",
        "![window.png](https://raw.githubusercontent.com/ID56/Torch-KWT/main/resources/window.png)\n",
        "\n",
        "While we don't have a long clip here, we can try **concatenating the three wavs** inside the `samples/` folder we made above into **a single 3s long audio clip**."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 61
        },
        "id": "BEe2SKUzEnvw",
        "outputId": "96991108-b132-4421-97e7-a7f1dd0fc59c"
      },
      "source": [
        "from IPython.display import Audio\n",
        "import soundfile as sf\n",
        "import numpy as np\n",
        "import librosa\n",
        "import glob\n",
        "\n",
        "def concat_audio(audio_folder):\n",
        "    audio_list = []\n",
        "    for audio_file in glob.glob(f\"{audio_folder}/*.wav\"):\n",
        "       x = librosa.load(audio_file, sr=16000)[0]\n",
        "       x = librosa.util.fix_length(x, 16000)\n",
        "       audio_list.append(x)\n",
        "    long_audio = np.hstack(audio_list)\n",
        "    sf.write(\"long_audio.wav\", long_audio, 16000)\n",
        "\n",
        "concat_audio(\"samples/\")\n",
        "Audio(\"long_audio.wav\")"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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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>"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fSYnIQENH8uE"
      },
      "source": [
        "Now let's run `window_inference.py`. It can be run in three modes:\n",
        "\n",
        "- multi: saves all found predictions (default)\n",
        "- max: saves the \"most confident\" prediction (outputs only a single 'clipwise; prediction for the whole clip)\n",
        "- n_voting: saves the \"most frequent\" prediction (outputs only a single 'clipwise' prediction for the whole clip)\n",
        "\n",
        "The `multi` mode is probably the most useful, and is thus the default mode. We will run inferences over **1s windows**, and **slide the window by 0.5s**. We will only keep the predictions with **confidence over 0.85**."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "da3PXJF_H8Uz",
        "outputId": "c0fe6f68-d5b3-402a-bd82-b28ab1de0f16"
      },
      "source": [
        "!python window_inference.py --conf sample_configs/base_config.yaml \\\n",
        "                     --ckpt kwmlp_pretrained.ckpt \\\n",
        "                     --inp long_audio.wav \\\n",
        "                     --out outputs/long_audio/ \\\n",
        "                     --lmap label_map.json \\\n",
        "                     --device cpu \\\n",
        "                     --wlen 1 \\\n",
        "                     --stride 0.5 \\\n",
        "                     --thresh 0.85 \\\n",
        "                     --mode multi"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved preds to outputs/long_audio/preds_clip.json\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FLLf4dUIIZwX",
        "outputId": "51d25ab8-1364-4bf3-fd45-dbb8e717d5f5"
      },
      "source": [
        "!cat outputs/long_audio/preds_clip.json"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{\"long_audio.wav\": [[\"one\", 0.9001082181930542, 0.0, 16000.0], [\"left\", 0.8915184140205383, 16000.0, 32000.0], [\"down\", 0.9065350890159607, 32000.0, 48000.0]]}"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f9jHlgjCJz1h"
      },
      "source": [
        "- Outputs are in the form: **[class, confidence, start_sample, end_sample]**. (If you divide sample by sample rate, you can get the time range)\n",
        "- It is possible that sometimes two windows may both partially fall on the same keyword instance. In such a case, you may get two consecutive predictions of the same class with some overlap. *(Like, nine-1s-2s and nine-1.5s-2.5s.)*\n",
        "- Similar to `inference.py` the `--inp` argument in `window_inference.py` can also work with a folder of audio files\n",
        "- You can also set the --batch_size argument for faster inference on GPU"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CUYdSxgpY6Mm"
      },
      "source": [
        "## Training\n",
        "\n",
        "For training, we only need to provide the config file."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oS8NAS4kclsA"
      },
      "source": [
        "### 9. Setting Up Your Config File\n",
        "\n",
        "For this example, we'll follow the `sample_configs/base_config.yaml`. In fact, you should be able to use this config to reproduce the results of the provided pretrained checkpoint if you follow the exact settings (training for 140 epochs @ batch_size = 256).\n",
        "\n",
        "We'll be training for 10 epochs in this example.\n",
        "\n",
        "You can also use [wandb](wandb.ai) to log your runs. Either provide a path to a txt file containing your API key, or set the env variable \"WANDB_API_KEY\", like:\n",
        "\n",
        "```\n",
        "os.environ[\"WANDB_API_KEY\"] = \"yourkey\"\n",
        "```\n",
        "\n",
        "We will not be using wandb in this example, but feel free to try it."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q3fYqLQQYlds"
      },
      "source": [
        "conf_str = \"\"\"# sample config to run a demo training of 10 epochs\n",
        "\n",
        "data_root: ./data/\n",
        "train_list_file: ./data/training_list.txt\n",
        "val_list_file: ./data/validation_list.txt\n",
        "test_list_file: ./data/testing_list.txt\n",
        "label_map: ./data/label_map.json\n",
        "\n",
        "exp:\n",
        "    wandb: False\n",
        "    wandb_api_key:\n",
        "    proj_name: torch-kw-mlp\n",
        "    exp_dir: ./runs\n",
        "    exp_name: kw-mlp-0.1.0\n",
        "    device: auto\n",
        "    log_freq: 20  # steps\n",
        "    log_to_file: False\n",
        "    log_to_stdout: True\n",
        "    val_freq: 1   # epochs\n",
        "    n_workers: 2\n",
        "    pin_memory: True\n",
        "    cache: 2      # 0 -> no cache | 1 -> cache wavs | 2 -> cache specs; stops wav augments\n",
        "    \n",
        "\n",
        "hparams:\n",
        "    restore_ckpt:\n",
        "    seed: 0\n",
        "    batch_size: 256\n",
        "    start_epoch: 0\n",
        "    n_epochs: 10\n",
        "    l_smooth: 0.1\n",
        "\n",
        "    audio:\n",
        "        sr: 16000\n",
        "        n_mels: 40\n",
        "        n_fft: 480\n",
        "        win_length: 480\n",
        "        hop_length: 160\n",
        "        center: False\n",
        "    \n",
        "    model:\n",
        "        type: kw-mlp \n",
        "        input_res: [40, 98]\n",
        "        patch_res: [40, 1]\n",
        "        num_classes: 35\n",
        "        channels: 1\n",
        "        dim: 64\n",
        "        depth: 12\n",
        "        pre_norm: False\n",
        "        prob_survival: 0.9\n",
        "\n",
        "    optimizer:\n",
        "        opt_type: adamw\n",
        "        opt_kwargs:\n",
        "          lr: 0.001\n",
        "          weight_decay: 0.1\n",
        "    \n",
        "    scheduler:\n",
        "        n_warmup: 10\n",
        "        max_epochs: 140\n",
        "        scheduler_type: cosine_annealing\n",
        "\n",
        "    augment:\n",
        "        spec_aug:\n",
        "            n_time_masks: 2\n",
        "            time_mask_width: 25\n",
        "            n_freq_masks: 2\n",
        "            freq_mask_width: 7\"\"\"\n",
        "\n",
        "!mkdir -p configs\n",
        "with open(\"configs/kwmlp_colab.yaml\", \"w+\") as f:\n",
        "  f.write(conf_str)"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FX6yUTn2cyaF"
      },
      "source": [
        "### 10. Initiating Training\n",
        "\n",
        "Make sure you are using a GPU runtime.\n",
        "\n",
        "In order to train to a full 140 epochs like the paper, on free resources, we need to cut down on disk I/O and audio processing time. So, we'll preemptively convert all our `.wav` files into MFCCs of shape `(40, 98)` and keep them stored in memory. This caching process may take ~6 minutes.\n",
        "\n",
        "We'll be using only spectral augmentation, like the paper."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NSasLdmVnmxZ"
      },
      "source": [
        "\n",
        "\n",
        "> Note: You may notice a \"Warning: Leaking Caffe2 thread-pool after fork.\" message after each epoch. It seems to be an existing torch-1.9 issue, which you can ignore. [See more here.](https://github.com/pytorch/pytorch/issues/57273)\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mZhtrxH4cQx2",
        "outputId": "3197cb8c-b195-4794-cbee-9a5a17024588"
      },
      "source": [
        "!python train.py --conf configs/kwmlp_colab.yaml"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Set seed 0\n",
            "Using settings:\n",
            " data_root: ./data/\n",
            "exp:\n",
            "  cache: 2\n",
            "  device: &id001 !!python/object/apply:torch.device\n",
            "  - cuda\n",
            "  exp_dir: ./runs\n",
            "  exp_name: kw-mlp-0.1.0\n",
            "  log_freq: 20\n",
            "  log_to_file: false\n",
            "  log_to_stdout: true\n",
            "  n_workers: 2\n",
            "  pin_memory: true\n",
            "  proj_name: torch-kw-mlp\n",
            "  save_dir: ./runs/kw-mlp-0.1.0\n",
            "  val_freq: 1\n",
            "  wandb: false\n",
            "  wandb_api_key: null\n",
            "hparams:\n",
            "  audio:\n",
            "    center: false\n",
            "    hop_length: 160\n",
            "    n_fft: 480\n",
            "    n_mels: 40\n",
            "    sr: 16000\n",
            "    win_length: 480\n",
            "  augment:\n",
            "    spec_aug:\n",
            "      freq_mask_width: 7\n",
            "      n_freq_masks: 2\n",
            "      n_time_masks: 2\n",
            "      time_mask_width: 25\n",
            "  batch_size: 256\n",
            "  device: *id001\n",
            "  l_smooth: 0.1\n",
            "  model:\n",
            "    channels: 1\n",
            "    depth: 12\n",
            "    dim: 64\n",
            "    input_res:\n",
            "    - 40\n",
            "    - 98\n",
            "    num_classes: 35\n",
            "    patch_res:\n",
            "    - 40\n",
            "    - 1\n",
            "    pre_norm: false\n",
            "    prob_survival: 0.9\n",
            "    type: kw-mlp\n",
            "  n_epochs: 10\n",
            "  optimizer:\n",
            "    opt_kwargs:\n",
            "      lr: 0.001\n",
            "      weight_decay: 0.1\n",
            "    opt_type: adamw\n",
            "  restore_ckpt: null\n",
            "  scheduler:\n",
            "    max_epochs: 140\n",
            "    n_warmup: 10\n",
            "    scheduler_type: cosine_annealing\n",
            "  seed: 0\n",
            "  start_epoch: 0\n",
            "label_map: ./data/label_map.json\n",
            "test_list_file: ./data/testing_list.txt\n",
            "train_list_file: ./data/training_list.txt\n",
            "val_list_file: ./data/validation_list.txt\n",
            "\n",
            "Caching dataset into memory.\n",
            "100% 84843/84843 [05:43<00:00, 247.16it/s]\n",
            "Caching dataset into memory.\n",
            "100% 9981/9981 [00:40<00:00, 247.70it/s]\n",
            "Caching dataset into memory.\n",
            "100% 11005/11005 [00:44<00:00, 247.67it/s]\n",
            "Created model with 424811 parameters.\n",
            "Initiating training.\n",
            "/usr/local/lib/python3.7/dist-packages/torch/optim/lr_scheduler.py:134: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n",
            "  \"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\", UserWarning)\n",
            "Step: 0 | epoch: 0 | loss: 3.6580820083618164 | lr: 3.012048192762012e-07\n",
            "Step: 20 | epoch: 0 | loss: 3.6794662475585938 | lr: 6.325301204800226e-06\n",
            "Step: 40 | epoch: 0 | loss: 3.6614067554473877 | lr: 1.234939759032425e-05\n",
            "Step: 60 | epoch: 0 | loss: 3.6613974571228027 | lr: 1.837349397584827e-05\n",
            "Step: 80 | epoch: 0 | loss: 3.605806827545166 | lr: 2.4397590361372296e-05\n",
            "Step: 100 | epoch: 0 | loss: 3.6321797370910645 | lr: 3.0421686746896325e-05\n",
            "Step: 120 | epoch: 0 | loss: 3.593381404876709 | lr: 3.644578313242034e-05\n",
            "Step: 140 | epoch: 0 | loss: 3.5892105102539062 | lr: 4.246987951794437e-05\n",
            "Step: 160 | epoch: 0 | loss: 3.5454163551330566 | lr: 4.849397590346839e-05\n",
            "Step: 180 | epoch: 0 | loss: 3.5461416244506836 | lr: 5.4518072288992414e-05\n",
            "Step: 200 | epoch: 0 | loss: 3.522672653198242 | lr: 6.054216867451644e-05\n",
            "Step: 220 | epoch: 0 | loss: 3.5552444458007812 | lr: 6.656626506004047e-05\n",
            "Step: 240 | epoch: 0 | loss: 3.515742778778076 | lr: 7.259036144556449e-05\n",
            "Step: 260 | epoch: 0 | loss: 3.502004861831665 | lr: 7.861445783108851e-05\n",
            "Step: 280 | epoch: 0 | loss: 3.500199317932129 | lr: 8.463855421661254e-05\n",
            "Step: 300 | epoch: 0 | loss: 3.498370409011841 | lr: 9.066265060213656e-05\n",
            "Step: 320 | epoch: 0 | loss: 3.5213804244995117 | lr: 9.668674698766059e-05\n",
            "Step: 332 | epoch: 0 | time_per_epoch: 75.61981296539307 | train_acc: 0.043197435262779485 | avg_loss_per_ep: 3.568134172853217\n",
            "  0% 0/39 [00:00<?, ?it/s][W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "100% 39/39 [00:03<00:00, 10.77it/s]\n",
            "Step: 332 | epoch: 0 | val_loss: 3.495259242180066 | val_acc: 0.06291954713956517\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.06291954713956517.\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "Step: 340 | epoch: 1 | loss: 3.4928722381591797 | lr: 0.00010271084337318461\n",
            "Step: 360 | epoch: 1 | loss: 3.5018324851989746 | lr: 0.00010873493975870863\n",
            "Step: 380 | epoch: 1 | loss: 3.4723005294799805 | lr: 0.00011475903614423266\n",
            "Step: 400 | epoch: 1 | loss: 3.4689958095550537 | lr: 0.00012078313252975669\n",
            "Step: 420 | epoch: 1 | loss: 3.4193115234375 | lr: 0.00012680722891528071\n",
            "Step: 440 | epoch: 1 | loss: 3.415942907333374 | lr: 0.00013283132530080474\n",
            "Step: 460 | epoch: 1 | loss: 3.458085536956787 | lr: 0.00013885542168632877\n",
            "Step: 480 | epoch: 1 | loss: 3.392547607421875 | lr: 0.00014487951807185277\n",
            "Step: 500 | epoch: 1 | loss: 3.3774662017822266 | lr: 0.0001509036144573768\n",
            "Step: 520 | epoch: 1 | loss: 3.3200125694274902 | lr: 0.00015692771084290083\n",
            "Step: 540 | epoch: 1 | loss: 3.2964916229248047 | lr: 0.00016295180722842486\n",
            "Step: 560 | epoch: 1 | loss: 3.267559051513672 | lr: 0.00016897590361394889\n",
            "Step: 580 | epoch: 1 | loss: 3.25459885597229 | lr: 0.00017499999999947289\n",
            "Step: 600 | epoch: 1 | loss: 3.2215328216552734 | lr: 0.00018102409638499691\n",
            "Step: 620 | epoch: 1 | loss: 3.1874375343322754 | lr: 0.00018704819277052094\n",
            "Step: 640 | epoch: 1 | loss: 3.1653451919555664 | lr: 0.00019307228915604497\n",
            "Step: 660 | epoch: 1 | loss: 3.079989194869995 | lr: 0.000199096385541569\n",
            "Step: 664 | epoch: 1 | time_per_epoch: 74.8010802268982 | train_acc: 0.11335054158858127 | avg_loss_per_ep: 3.341925572199994\n",
            "  0% 0/39 [00:00<?, ?it/s][W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "100% 39/39 [00:03<00:00, 10.77it/s]\n",
            "Step: 664 | epoch: 1 | val_loss: 3.1179219759427586 | val_acc: 0.211401663160004\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.211401663160004.\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "Step: 680 | epoch: 2 | loss: 3.054649829864502 | lr: 0.00020512048192709303\n",
            "Step: 700 | epoch: 2 | loss: 3.1029856204986572 | lr: 0.00021114457831261706\n",
            "Step: 720 | epoch: 2 | loss: 3.1771204471588135 | lr: 0.00021716867469814106\n",
            "Step: 740 | epoch: 2 | loss: 3.0819482803344727 | lr: 0.00022319277108366509\n",
            "Step: 760 | epoch: 2 | loss: 3.0498998165130615 | lr: 0.00022921686746918911\n",
            "Step: 780 | epoch: 2 | loss: 3.0438902378082275 | lr: 0.00023524096385471314\n",
            "Step: 800 | epoch: 2 | loss: 2.9589128494262695 | lr: 0.00024126506024023717\n",
            "Step: 820 | epoch: 2 | loss: 2.864346504211426 | lr: 0.0002472891566257612\n",
            "Step: 840 | epoch: 2 | loss: 2.9903314113616943 | lr: 0.0002533132530112852\n",
            "Step: 860 | epoch: 2 | loss: 2.7676265239715576 | lr: 0.00025933734939680923\n",
            "Step: 880 | epoch: 2 | loss: 2.9047904014587402 | lr: 0.0002653614457823333\n",
            "Step: 900 | epoch: 2 | loss: 2.9003214836120605 | lr: 0.0002713855421678573\n",
            "Step: 920 | epoch: 2 | loss: 2.868509292602539 | lr: 0.00027740963855338134\n",
            "Step: 940 | epoch: 2 | loss: 2.8282899856567383 | lr: 0.00028343373493890534\n",
            "Step: 960 | epoch: 2 | loss: 2.733224630355835 | lr: 0.00028945783132442934\n",
            "Step: 980 | epoch: 2 | loss: 2.7022974491119385 | lr: 0.0002954819277099534\n",
            "Step: 996 | epoch: 2 | time_per_epoch: 74.98275446891785 | train_acc: 0.2360359723253539 | avg_loss_per_ep: 2.925249497574496\n",
            "  0% 0/39 [00:00<?, ?it/s][W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
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            "100% 39/39 [00:03<00:00, 10.80it/s]\n",
            "Step: 996 | epoch: 2 | val_loss: 2.4975273670294347 | val_acc: 0.41128143472597933\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.41128143472597933.\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "Step: 1000 | epoch: 3 | loss: 2.548206090927124 | lr: 0.00030150602409547745\n",
            "Step: 1020 | epoch: 3 | loss: 2.670149326324463 | lr: 0.00030753012048100146\n",
            "Step: 1040 | epoch: 3 | loss: 2.5429463386535645 | lr: 0.0003135542168665254\n",
            "Step: 1060 | epoch: 3 | loss: 2.6670708656311035 | lr: 0.00031957831325204946\n",
            "Step: 1080 | epoch: 3 | loss: 2.458192825317383 | lr: 0.00032560240963757346\n",
            "Step: 1100 | epoch: 3 | loss: 2.5198822021484375 | lr: 0.0003316265060230975\n",
            "Step: 1120 | epoch: 3 | loss: 2.4257588386535645 | lr: 0.00033765060240862157\n",
            "Step: 1140 | epoch: 3 | loss: 2.501819133758545 | lr: 0.00034367469879414557\n",
            "Step: 1160 | epoch: 3 | loss: 2.4283499717712402 | lr: 0.0003496987951796696\n",
            "Step: 1180 | epoch: 3 | loss: 2.51840877532959 | lr: 0.00035572289156519363\n",
            "Step: 1200 | epoch: 3 | loss: 2.4455032348632812 | lr: 0.0003617469879507177\n",
            "Step: 1220 | epoch: 3 | loss: 2.217632293701172 | lr: 0.0003677710843362417\n",
            "Step: 1240 | epoch: 3 | loss: 2.2677884101867676 | lr: 0.00037379518072176574\n",
            "Step: 1260 | epoch: 3 | loss: 2.1961400508880615 | lr: 0.00037981927710728974\n",
            "Step: 1280 | epoch: 3 | loss: 2.285163402557373 | lr: 0.0003858433734928137\n",
            "Step: 1300 | epoch: 3 | loss: 2.3404111862182617 | lr: 0.00039186746987833774\n",
            "Step: 1320 | epoch: 3 | loss: 2.0271408557891846 | lr: 0.00039789156626386174\n",
            "Step: 1328 | epoch: 3 | time_per_epoch: 74.59922862052917 | train_acc: 0.40846033261435827 | avg_loss_per_ep: 2.409277021884918\n",
            "  0% 0/39 [00:00<?, ?it/s][W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
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            "100% 39/39 [00:03<00:00, 10.80it/s]\n",
            "Step: 1328 | epoch: 3 | val_loss: 1.6719141556666448 | val_acc: 0.6950205390241458\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.6950205390241458.\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "Step: 1340 | epoch: 4 | loss: 2.094409942626953 | lr: 0.0004039156626493858\n",
            "Step: 1360 | epoch: 4 | loss: 2.101273536682129 | lr: 0.00040993975903490986\n",
            "Step: 1380 | epoch: 4 | loss: 2.079681873321533 | lr: 0.00041596385542043386\n",
            "Step: 1400 | epoch: 4 | loss: 1.975559115409851 | lr: 0.0004219879518059579\n",
            "Step: 1420 | epoch: 4 | loss: 2.0820107460021973 | lr: 0.0004280120481914819\n",
            "Step: 1440 | epoch: 4 | loss: 2.140676975250244 | lr: 0.00043403614457700597\n",
            "Step: 1460 | epoch: 4 | loss: 2.3004322052001953 | lr: 0.00044006024096252997\n",
            "Step: 1480 | epoch: 4 | loss: 1.9699411392211914 | lr: 0.000446084337348054\n",
            "Step: 1500 | epoch: 4 | loss: 1.8654935359954834 | lr: 0.000452108433733578\n",
            "Step: 1520 | epoch: 4 | loss: 2.296445846557617 | lr: 0.0004581325301191021\n",
            "Step: 1540 | epoch: 4 | loss: 1.9552857875823975 | lr: 0.00046415662650462603\n",
            "Step: 1560 | epoch: 4 | loss: 1.9141850471496582 | lr: 0.00047018072289015003\n",
            "Step: 1580 | epoch: 4 | loss: 1.82753324508667 | lr: 0.0004762048192756741\n",
            "Step: 1600 | epoch: 4 | loss: 1.9090999364852905 | lr: 0.00048222891566119814\n",
            "Step: 1620 | epoch: 4 | loss: 1.6680679321289062 | lr: 0.00048825301204672214\n",
            "Step: 1640 | epoch: 4 | loss: 1.7069482803344727 | lr: 0.0004942771084322461\n",
            "Step: 1660 | epoch: 4 | time_per_epoch: 74.35615706443787 | train_acc: 0.5548719399361173 | avg_loss_per_ep: 1.9761173696403045\n",
            "  0% 0/39 [00:00<?, ?it/s][W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
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            "100% 39/39 [00:03<00:00, 10.83it/s]\n",
            "Step: 1660 | epoch: 4 | val_loss: 1.270777201041197 | val_acc: 0.8199579200480914\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.8199579200480914.\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
            "Step: 1660 | epoch: 5 | loss: 1.760310173034668 | lr: 0.0005003012048177703\n",
            "Step: 1680 | epoch: 5 | loss: 1.7140841484069824 | lr: 0.0005063253012032943\n",
            "Step: 1700 | epoch: 5 | loss: 2.0193417072296143 | lr: 0.0005123493975888183\n",
            "Step: 1720 | epoch: 5 | loss: 1.6365423202514648 | lr: 0.0005183734939743423\n",
            "Step: 1740 | epoch: 5 | loss: 1.7051745653152466 | lr: 0.0005243975903598664\n",
            "Step: 1760 | epoch: 5 | loss: 1.8625309467315674 | lr: 0.0005304216867453904\n",
            "Step: 1780 | epoch: 5 | loss: 1.7218047380447388 | lr: 0.0005364457831309144\n",
            "Step: 1800 | epoch: 5 | loss: 1.5547373294830322 | lr: 0.0005424698795164384\n",
            "Step: 1820 | epoch: 5 | loss: 1.6985664367675781 | lr: 0.0005484939759019624\n",
            "Step: 1840 | epoch: 5 | loss: 1.6681463718414307 | lr: 0.0005545180722874864\n",
            "Step: 1860 | epoch: 5 | loss: 1.8171436786651611 | lr: 0.0005605421686730105\n",
            "Step: 1880 | epoch: 5 | loss: 1.8614897727966309 | lr: 0.0005665662650585345\n",
            "Step: 1900 | epoch: 5 | loss: 1.6181671619415283 | lr: 0.0005725903614440585\n",
            "Step: 1920 | epoch: 5 | loss: 1.7363970279693604 | lr: 0.0005786144578295825\n",
            "Step: 1940 | epoch: 5 | loss: 1.893572449684143 | lr: 0.0005846385542151066\n",
            "Step: 1960 | epoch: 5 | loss: 1.631476640701294 | lr: 0.0005906626506006306\n",
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            "Step: 1992 | epoch: 5 | time_per_epoch: 74.66522645950317 | train_acc: 0.6381433942694152 | avg_loss_per_ep: 1.7295661144945995\n",
            "  0% 0/39 [00:00<?, ?it/s][W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
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            "Step: 1992 | epoch: 5 | val_loss: 1.1033175113873603 | val_acc: 0.8678489129345757\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.8678489129345757.\n",
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            "Step: 2000 | epoch: 6 | loss: 1.6551096439361572 | lr: 0.0006027108433716786\n",
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            "Step: 2324 | epoch: 6 | time_per_epoch: 75.37205648422241 | train_acc: 0.6936694836344778 | avg_loss_per_ep: 1.5709703115813702\n",
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            "Step: 2324 | epoch: 6 | val_loss: 1.0647127781158838 | val_acc: 0.877266806933173\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.877266806933173.\n",
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            "Step: 2340 | epoch: 7 | loss: 1.341969609260559 | lr: 0.0007051204819255871\n",
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            "Step: 2656 | epoch: 7 | time_per_epoch: 74.31023502349854 | train_acc: 0.7215327133646854 | avg_loss_per_ep: 1.4898257456630108\n",
            "  0% 0/39 [00:00<?, ?it/s][W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n",
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            "Step: 2656 | epoch: 7 | val_loss: 0.9795123384549067 | val_acc: 0.9070233443542731\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.9070233443542731.\n",
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            "Step: 2660 | epoch: 8 | loss: 1.334463357925415 | lr: 0.0008015060240939714\n",
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            "Step: 2988 | epoch: 8 | time_per_epoch: 75.55728459358215 | train_acc: 0.7511049821434885 | avg_loss_per_ep: 1.4045602413545173\n",
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            "Step: 2988 | epoch: 8 | val_loss: 0.9333042059189234 | val_acc: 0.9218515178839796\n",
            "Saved ./runs/kw-mlp-0.1.0/best.pth with accuracy 0.9218515178839796.\n",
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            "Step: 3000 | epoch: 9 | loss: 1.3188233375549316 | lr: 0.0009039156626478797\n",
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            "Step: 3320 | epoch: 9 | time_per_epoch: 74.746173620224 | train_acc: 0.7675589029147956 | avg_loss_per_ep: 1.3529038745236683\n",
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            "Step: 3320 | epoch: 9 | val_loss: 0.9351714910605015 | val_acc: 0.916240857629496\n",
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            "Step: 3320 | epoch: 9 | val_loss: 0.9351714910605015 | val_acc: 0.916240857629496\n",
            "Saved ./runs/kw-mlp-0.1.0/last.pth with accuracy 0.916240857629496.\n",
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            "Step: 3652 | test_loss_last: 0.9744662628617398 | test_acc_last: 0.9010449795547478\n",
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            "Step: 3652 | test_loss_best: 0.9765181818673777 | test_acc_best: 0.906133575647433\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2o9uS25poupC"
      },
      "source": [
        "After training 10 epochs, we have a validation accuracy of **~91.6%** and a test accuracy of **~90.1%**.\n",
        "\n",
        "\n",
        "In colab, it takes **~75 s** per epoch, with an additional **~3 s** for validation. To do a complete training like the paper (140 epochs) on colab, you'd thus need around **3 hours**.\n",
        "\n",
        "You may also try training KW-MLP on Kaggle, which I've found to be notably faster. Full training takes around **2 hours** there."
      ]
    }
  ]
}