mvcnn_pytorch.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "mvcnn_pytorch.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "machine_shape": "hm",
      "mount_file_id": "1b9h1IwGlPmubaLjZdpWr2WGxZg89UiUn",
      "authorship_tag": "ABX9TyM7EGwrIytf7NNgxvTT0k9Z",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/DIPTE/Deep-Geometry-Learning-on-Colab/blob/master/mvcnn_pytorch.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r4oS_mtz2ewq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "28ba7ef6-315a-456f-9639-160eb118b1af"
      },
      "source": [
        "!ls"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "__init__.py  models  README.md\ttools  train_mvcnn.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i97jdBJk2vAW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import os\n",
        "os.chdir('/content/drive/My Drive')#切换工作目录"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cG-Nabwh20EZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!git clone https://github.com/jongchyisu/mvcnn_pytorch.git"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WP9xFeF03lRd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import os\n",
        "os.chdir('/content/drive/My Drive/mvcnn_pytorch/')#切换工作目录"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HNF4tIuj30Du",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import sys\n",
        "cur = '/content/drive/My Drive/mvcnn_pytorch'\n",
        "sys.path.append(cur)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sqgU20vDBfI9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "888b5a3c-9653-4ed1-d52f-2157a1cc2c92"
      },
      "source": [
        "!wget http://supermoe.cs.umass.edu/shape_recog/shaded_images.tar.gz && tar -xzvf shaded_images.tar.gz"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[1;30;43m流式输出内容被截断，只能显示最后 5000 行内容。\u001b[0m\n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "emiQ2AOMF08m",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 188
        },
        "outputId": "b71c7ba0-4ac1-4dd8-f5d3-94e55f179417"
      },
      "source": [
        "!pip install tensorboardX"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting tensorboardX\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/af/0c/4f41bcd45db376e6fe5c619c01100e9b7531c55791b7244815bac6eac32c/tensorboardX-2.1-py2.py3-none-any.whl (308kB)\n",
            "\r\u001b[K     |█                               | 10kB 22.8MB/s eta 0:00:01\r\u001b[K     |██▏                             | 20kB 1.6MB/s eta 0:00:01\r\u001b[K     |███▏                            | 30kB 1.8MB/s eta 0:00:01\r\u001b[K     |████▎                           | 40kB 2.1MB/s eta 0:00:01\r\u001b[K     |█████▎                          | 51kB 2.0MB/s eta 0:00:01\r\u001b[K     |██████▍                         | 61kB 2.2MB/s eta 0:00:01\r\u001b[K     |███████▍                        | 71kB 2.4MB/s eta 0:00:01\r\u001b[K     |████████▌                       | 81kB 2.6MB/s eta 0:00:01\r\u001b[K     |█████████▌                      | 92kB 2.5MB/s eta 0:00:01\r\u001b[K     |██████████▋                     | 102kB 2.6MB/s eta 0:00:01\r\u001b[K     |███████████▊                    | 112kB 2.6MB/s eta 0:00:01\r\u001b[K     |████████████▊                   | 122kB 2.6MB/s eta 0:00:01\r\u001b[K     |█████████████▉                  | 133kB 2.6MB/s eta 0:00:01\r\u001b[K     |██████████████▉                 | 143kB 2.6MB/s eta 0:00:01\r\u001b[K     |████████████████                | 153kB 2.6MB/s eta 0:00:01\r\u001b[K     |█████████████████               | 163kB 2.6MB/s eta 0:00:01\r\u001b[K     |██████████████████              | 174kB 2.6MB/s eta 0:00:01\r\u001b[K     |███████████████████             | 184kB 2.6MB/s eta 0:00:01\r\u001b[K     |████████████████████▏           | 194kB 2.6MB/s eta 0:00:01\r\u001b[K     |█████████████████████▎          | 204kB 2.6MB/s eta 0:00:01\r\u001b[K     |██████████████████████▎         | 215kB 2.6MB/s eta 0:00:01\r\u001b[K     |███████████████████████▍        | 225kB 2.6MB/s eta 0:00:01\r\u001b[K     |████████████████████████▍       | 235kB 2.6MB/s eta 0:00:01\r\u001b[K     |█████████████████████████▌      | 245kB 2.6MB/s eta 0:00:01\r\u001b[K     |██████████████████████████▌     | 256kB 2.6MB/s eta 0:00:01\r\u001b[K     |███████████████████████████▋    | 266kB 2.6MB/s eta 0:00:01\r\u001b[K     |████████████████████████████▋   | 276kB 2.6MB/s eta 0:00:01\r\u001b[K     |█████████████████████████████▊  | 286kB 2.6MB/s eta 0:00:01\r\u001b[K     |██████████████████████████████▊ | 296kB 2.6MB/s eta 0:00:01\r\u001b[K     |███████████████████████████████▉| 307kB 2.6MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 317kB 2.6MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from tensorboardX) (1.18.5)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from tensorboardX) (1.12.0)\n",
            "Requirement already satisfied: protobuf>=3.8.0 in /usr/local/lib/python3.6/dist-packages (from tensorboardX) (3.12.2)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.8.0->tensorboardX) (49.1.0)\n",
            "Installing collected packages: tensorboardX\n",
            "Successfully installed tensorboardX-2.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2ittqmvRFwlO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "4757a834-5feb-40c6-d6e7-8bed1e4ed89d"
      },
      "source": [
        "!python train_mvcnn.py -name mvcnn -num_models 1000 -weight_decay 0.001 -num_views 12 -cnn_name vgg11"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: \"https://download.pytorch.org/models/vgg11-bbd30ac9.pth\" to /root/.cache/torch/checkpoints/vgg11-bbd30ac9.pth\n",
            "100% 507M/507M [00:07<00:00, 67.9MB/s]\n",
            "num_train_files: 118116\n",
            "num_val_files: 29616\n",
            "epoch 1, step 1: train_loss 3.948; train_acc 0.016\n",
            "epoch 1, step 2: train_loss 3.766; train_acc 0.047\n",
            "epoch 1, step 3: train_loss 3.615; train_acc 0.141\n",
            "epoch 1, step 4: train_loss 3.584; train_acc 0.047\n",
            "epoch 1, step 5: train_loss 3.415; train_acc 0.141\n",
            "epoch 1, step 6: train_loss 3.505; train_acc 0.172\n",
            "epoch 1, step 7: train_loss 3.579; train_acc 0.094\n",
            "epoch 1, step 8: train_loss 3.369; train_acc 0.188\n",
            "epoch 1, step 9: train_loss 3.356; train_acc 0.094\n",
            "epoch 1, step 10: train_loss 3.312; train_acc 0.141\n",
            "epoch 1, step 11: train_loss 3.084; train_acc 0.266\n",
            "epoch 1, step 12: train_loss 3.179; train_acc 0.172\n",
            "epoch 1, step 13: train_loss 3.121; train_acc 0.172\n",
            "epoch 1, step 14: train_loss 3.090; train_acc 0.219\n",
            "epoch 1, step 15: train_loss 2.962; train_acc 0.203\n",
            "epoch 1, step 16: train_loss 2.803; train_acc 0.234\n",
            "epoch 1, step 17: train_loss 2.967; train_acc 0.281\n",
            "epoch 1, step 18: train_loss 2.766; train_acc 0.266\n",
            "epoch 1, step 19: train_loss 2.521; train_acc 0.375\n",
            "epoch 1, step 20: train_loss 2.529; train_acc 0.359\n",
            "epoch 1, step 21: train_loss 2.447; train_acc 0.375\n",
            "epoch 1, step 22: train_loss 2.633; train_acc 0.297\n",
            "epoch 1, step 23: train_loss 2.623; train_acc 0.250\n",
            "epoch 1, step 24: train_loss 2.474; train_acc 0.328\n",
            "epoch 1, step 25: train_loss 2.306; train_acc 0.484\n",
            "epoch 1, step 26: train_loss 2.415; train_acc 0.406\n",
            "epoch 1, step 27: train_loss 2.357; train_acc 0.422\n",
            "epoch 1, step 28: train_loss 2.313; train_acc 0.484\n",
            "epoch 1, step 29: train_loss 2.028; train_acc 0.516\n",
            "epoch 1, step 30: train_loss 2.277; train_acc 0.469\n",
            "epoch 1, step 31: train_loss 2.183; train_acc 0.422\n",
            "epoch 1, step 32: train_loss 1.879; train_acc 0.562\n",
            "epoch 1, step 33: train_loss 2.136; train_acc 0.422\n",
            "epoch 1, step 34: train_loss 1.696; train_acc 0.594\n",
            "epoch 1, step 35: train_loss 1.950; train_acc 0.516\n",
            "epoch 1, step 36: train_loss 1.918; train_acc 0.438\n",
            "epoch 1, step 37: train_loss 2.142; train_acc 0.469\n",
            "epoch 1, step 38: train_loss 2.019; train_acc 0.469\n",
            "epoch 1, step 39: train_loss 2.017; train_acc 0.438\n",
            "epoch 1, step 40: train_loss 1.568; train_acc 0.625\n",
            "epoch 1, step 41: train_loss 2.033; train_acc 0.453\n",
            "epoch 1, step 42: train_loss 1.746; train_acc 0.531\n",
            "epoch 1, step 43: train_loss 1.619; train_acc 0.516\n",
            "epoch 1, step 44: train_loss 1.572; train_acc 0.562\n",
            "epoch 1, step 45: train_loss 1.633; train_acc 0.578\n",
            "epoch 1, step 46: train_loss 1.456; train_acc 0.609\n",
            "epoch 1, step 47: train_loss 1.431; train_acc 0.656\n",
            "epoch 1, step 48: train_loss 1.749; train_acc 0.531\n",
            "epoch 1, step 49: train_loss 1.528; train_acc 0.609\n",
            "epoch 1, step 50: train_loss 1.729; train_acc 0.531\n",
            "epoch 1, step 51: train_loss 1.339; train_acc 0.609\n",
            "epoch 1, step 52: train_loss 0.926; train_acc 0.781\n",
            "epoch 1, step 53: train_loss 1.418; train_acc 0.656\n",
            "epoch 1, step 54: train_loss 1.510; train_acc 0.547\n",
            "epoch 1, step 55: train_loss 0.996; train_acc 0.719\n",
            "epoch 1, step 56: train_loss 1.104; train_acc 0.672\n",
            "epoch 1, step 57: train_loss 1.454; train_acc 0.609\n",
            "epoch 1, step 58: train_loss 1.110; train_acc 0.672\n",
            "epoch 1, step 59: train_loss 1.131; train_acc 0.672\n",
            "epoch 1, step 60: train_loss 1.101; train_acc 0.703\n",
            "epoch 1, step 61: train_loss 1.184; train_acc 0.625\n",
            "epoch 1, step 62: train_loss 1.169; train_acc 0.656\n",
            "epoch 1, step 63: train_loss 1.623; train_acc 0.484\n",
            "epoch 1, step 64: train_loss 1.317; train_acc 0.609\n",
            "epoch 1, step 65: train_loss 1.195; train_acc 0.656\n",
            "epoch 1, step 66: train_loss 1.360; train_acc 0.609\n",
            "epoch 1, step 67: train_loss 1.234; train_acc 0.594\n",
            "epoch 1, step 68: train_loss 1.257; train_acc 0.641\n",
            "epoch 1, step 69: train_loss 1.259; train_acc 0.641\n",
            "epoch 1, step 70: train_loss 1.191; train_acc 0.703\n",
            "epoch 1, step 71: train_loss 1.067; train_acc 0.734\n",
            "epoch 1, step 72: train_loss 1.036; train_acc 0.766\n",
            "epoch 1, step 73: train_loss 0.943; train_acc 0.750\n",
            "epoch 1, step 74: train_loss 0.958; train_acc 0.734\n",
            "epoch 1, step 75: train_loss 0.905; train_acc 0.734\n",
            "epoch 1, step 76: train_loss 0.706; train_acc 0.828\n",
            "epoch 1, step 77: train_loss 1.363; train_acc 0.656\n",
            "epoch 1, step 78: train_loss 1.034; train_acc 0.625\n",
            "epoch 1, step 79: train_loss 1.097; train_acc 0.656\n",
            "epoch 1, step 80: train_loss 1.044; train_acc 0.703\n",
            "epoch 1, step 81: train_loss 1.148; train_acc 0.719\n",
            "epoch 1, step 82: train_loss 1.275; train_acc 0.641\n",
            "epoch 1, step 83: train_loss 0.982; train_acc 0.766\n",
            "epoch 1, step 84: train_loss 1.182; train_acc 0.688\n",
            "epoch 1, step 85: train_loss 1.196; train_acc 0.656\n",
            "epoch 1, step 86: train_loss 1.004; train_acc 0.719\n",
            "epoch 1, step 87: train_loss 1.096; train_acc 0.719\n",
            "epoch 1, step 88: train_loss 1.130; train_acc 0.719\n",
            "epoch 1, step 89: train_loss 1.352; train_acc 0.594\n",
            "epoch 1, step 90: train_loss 0.939; train_acc 0.734\n",
            "epoch 1, step 91: train_loss 1.202; train_acc 0.625\n",
            "epoch 1, step 92: train_loss 1.213; train_acc 0.703\n",
            "epoch 1, step 93: train_loss 0.911; train_acc 0.734\n",
            "epoch 1, step 94: train_loss 1.044; train_acc 0.688\n",
            "epoch 1, step 95: train_loss 1.140; train_acc 0.672\n",
            "epoch 1, step 96: train_loss 1.392; train_acc 0.594\n",
            "epoch 1, step 97: train_loss 0.809; train_acc 0.812\n",
            "epoch 1, step 98: train_loss 0.950; train_acc 0.750\n",
            "epoch 1, step 99: train_loss 0.623; train_acc 0.828\n",
            "epoch 1, step 100: train_loss 1.029; train_acc 0.688\n",
            "epoch 1, step 101: train_loss 1.108; train_acc 0.672\n",
            "epoch 1, step 102: train_loss 0.807; train_acc 0.766\n",
            "epoch 1, step 103: train_loss 0.977; train_acc 0.688\n",
            "epoch 1, step 104: train_loss 0.951; train_acc 0.750\n",
            "epoch 1, step 105: train_loss 1.075; train_acc 0.656\n",
            "epoch 1, step 106: train_loss 0.661; train_acc 0.812\n",
            "epoch 1, step 107: train_loss 1.230; train_acc 0.656\n",
            "epoch 1, step 108: train_loss 0.970; train_acc 0.734\n",
            "epoch 1, step 109: train_loss 1.098; train_acc 0.688\n",
            "epoch 1, step 110: train_loss 0.896; train_acc 0.672\n",
            "epoch 1, step 111: train_loss 0.991; train_acc 0.703\n",
            "epoch 1, step 112: train_loss 1.095; train_acc 0.734\n",
            "epoch 1, step 113: train_loss 1.105; train_acc 0.703\n",
            "epoch 1, step 114: train_loss 0.766; train_acc 0.766\n",
            "epoch 1, step 115: train_loss 0.763; train_acc 0.734\n",
            "epoch 1, step 116: train_loss 1.007; train_acc 0.672\n",
            "epoch 1, step 117: train_loss 1.286; train_acc 0.594\n",
            "epoch 1, step 118: train_loss 0.968; train_acc 0.672\n",
            "epoch 1, step 119: train_loss 1.031; train_acc 0.734\n",
            "epoch 1, step 120: train_loss 0.867; train_acc 0.719\n",
            "epoch 1, step 121: train_loss 0.952; train_acc 0.766\n",
            "epoch 1, step 122: train_loss 0.892; train_acc 0.781\n",
            "epoch 1, step 123: train_loss 0.619; train_acc 0.859\n",
            "epoch 1, step 124: train_loss 0.742; train_acc 0.781\n",
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            "epoch 1, step 418: train_loss 0.344; train_acc 0.891\n",
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            "epoch 1, step 433: train_loss 0.426; train_acc 0.828\n",
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            "epoch 1, step 443: train_loss 0.778; train_acc 0.750\n",
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            "epoch 1, step 446: train_loss 0.699; train_acc 0.766\n",
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            "epoch 1, step 448: train_loss 0.255; train_acc 0.938\n",
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            "epoch 1, step 452: train_loss 0.528; train_acc 0.812\n",
            "epoch 1, step 453: train_loss 0.561; train_acc 0.812\n",
            "epoch 1, step 454: train_loss 0.371; train_acc 0.844\n",
            "epoch 1, step 455: train_loss 0.579; train_acc 0.812\n",
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            "epoch 1, step 457: train_loss 0.518; train_acc 0.797\n",
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            "epoch 1, step 460: train_loss 0.212; train_acc 0.953\n",
            "epoch 1, step 461: train_loss 0.629; train_acc 0.828\n",
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            "epoch 1, step 463: train_loss 0.206; train_acc 0.938\n",
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            "epoch 1, step 466: train_loss 0.503; train_acc 0.844\n",
            "epoch 1, step 467: train_loss 0.632; train_acc 0.797\n",
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            "epoch 1, step 469: train_loss 0.558; train_acc 0.844\n",
            "epoch 1, step 470: train_loss 0.508; train_acc 0.812\n",
            "epoch 1, step 471: train_loss 0.331; train_acc 0.906\n",
            "epoch 1, step 472: train_loss 0.547; train_acc 0.766\n",
            "epoch 1, step 473: train_loss 0.500; train_acc 0.844\n",
            "epoch 1, step 474: train_loss 0.548; train_acc 0.875\n",
            "epoch 1, step 475: train_loss 0.594; train_acc 0.844\n",
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            "epoch 1, step 477: train_loss 0.422; train_acc 0.875\n",
            "epoch 1, step 478: train_loss 0.337; train_acc 0.906\n",
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            "epoch 1, step 480: train_loss 0.602; train_acc 0.828\n",
            "epoch 1, step 481: train_loss 0.409; train_acc 0.875\n",
            "epoch 1, step 482: train_loss 0.392; train_acc 0.891\n",
            "epoch 1, step 483: train_loss 0.742; train_acc 0.750\n",
            "epoch 1, step 484: train_loss 0.389; train_acc 0.859\n",
            "epoch 1, step 485: train_loss 0.511; train_acc 0.859\n",
            "epoch 1, step 486: train_loss 0.595; train_acc 0.797\n",
            "epoch 1, step 487: train_loss 0.421; train_acc 0.906\n",
            "epoch 1, step 488: train_loss 0.376; train_acc 0.891\n",
            "epoch 1, step 489: train_loss 0.544; train_acc 0.812\n",
            "epoch 1, step 490: train_loss 0.216; train_acc 0.938\n",
            "epoch 1, step 491: train_loss 0.347; train_acc 0.891\n",
            "epoch 1, step 492: train_loss 0.547; train_acc 0.875\n",
            "epoch 1, step 493: train_loss 0.353; train_acc 0.922\n",
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            "epoch 1, step 495: train_loss 0.401; train_acc 0.875\n",
            "epoch 1, step 496: train_loss 0.425; train_acc 0.844\n",
            "epoch 1, step 497: train_loss 0.265; train_acc 0.922\n",
            "epoch 1, step 498: train_loss 0.403; train_acc 0.891\n",
            "epoch 1, step 499: train_loss 0.332; train_acc 0.906\n",
            "epoch 1, step 500: train_loss 0.611; train_acc 0.828\n",
            "epoch 1, step 501: train_loss 0.334; train_acc 0.906\n",
            "epoch 1, step 502: train_loss 0.487; train_acc 0.859\n",
            "epoch 1, step 503: train_loss 0.518; train_acc 0.844\n",
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            "epoch 1, step 506: train_loss 0.554; train_acc 0.812\n",
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            "epoch 1, step 508: train_loss 0.374; train_acc 0.875\n",
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            "epoch 1, step 510: train_loss 0.411; train_acc 0.875\n",
            "epoch 1, step 511: train_loss 0.287; train_acc 0.953\n",
            "epoch 1, step 512: train_loss 0.637; train_acc 0.797\n",
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            "epoch 1, step 515: train_loss 0.577; train_acc 0.859\n",
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            "epoch 1, step 519: train_loss 0.525; train_acc 0.844\n",
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            "epoch 1, step 521: train_loss 0.427; train_acc 0.875\n",
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            "epoch 1, step 524: train_loss 0.400; train_acc 0.891\n",
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            "epoch 1, step 527: train_loss 0.320; train_acc 0.906\n",
            "epoch 1, step 528: train_loss 0.561; train_acc 0.844\n",
            "epoch 1, step 529: train_loss 0.523; train_acc 0.781\n",
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            "epoch 1, step 531: train_loss 0.427; train_acc 0.828\n",
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            "epoch 1, step 534: train_loss 0.241; train_acc 0.891\n",
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            "epoch 1, step 536: train_loss 0.628; train_acc 0.859\n",
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            "epoch 1, step 553: train_loss 0.321; train_acc 0.906\n",
            "epoch 1, step 554: train_loss 0.396; train_acc 0.891\n",
            "epoch 1, step 555: train_loss 0.674; train_acc 0.828\n",
            "epoch 1, step 556: train_loss 0.434; train_acc 0.859\n",
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            "epoch 1, step 558: train_loss 0.379; train_acc 0.844\n",
            "epoch 1, step 559: train_loss 0.536; train_acc 0.828\n",
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            "epoch 1, step 564: train_loss 0.301; train_acc 0.875\n",
            "epoch 1, step 565: train_loss 0.459; train_acc 0.859\n",
            "epoch 1, step 566: train_loss 0.737; train_acc 0.812\n",
            "epoch 1, step 567: train_loss 0.417; train_acc 0.891\n",
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            "epoch 1, step 569: train_loss 0.406; train_acc 0.922\n",
            "epoch 1, step 570: train_loss 0.397; train_acc 0.859\n",
            "epoch 1, step 571: train_loss 0.351; train_acc 0.891\n",
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            "epoch 1, step 574: train_loss 0.487; train_acc 0.797\n",
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            "epoch 1, step 576: train_loss 0.674; train_acc 0.797\n",
            "epoch 1, step 577: train_loss 0.543; train_acc 0.812\n",
            "epoch 1, step 578: train_loss 0.225; train_acc 0.938\n",
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            "epoch 1, step 580: train_loss 0.538; train_acc 0.891\n",
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            "epoch 1, step 585: train_loss 0.421; train_acc 0.875\n",
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            "epoch 1, step 590: train_loss 0.475; train_acc 0.859\n",
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            "epoch 1, step 608: train_loss 0.679; train_acc 0.734\n",
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            "epoch 1, step 617: train_loss 0.218; train_acc 0.938\n",
            "epoch 1, step 618: train_loss 0.678; train_acc 0.781\n",
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            "epoch 1, step 620: train_loss 0.532; train_acc 0.844\n",
            "epoch 1, step 621: train_loss 0.421; train_acc 0.844\n",
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            "epoch 1, step 623: train_loss 0.405; train_acc 0.875\n",
            "epoch 1, step 624: train_loss 0.683; train_acc 0.781\n",
            "epoch 1, step 625: train_loss 0.164; train_acc 0.953\n",
            "epoch 1, step 626: train_loss 0.397; train_acc 0.906\n",
            "epoch 1, step 627: train_loss 0.398; train_acc 0.922\n",
            "epoch 1, step 628: train_loss 0.254; train_acc 0.922\n",
            "epoch 1, step 629: train_loss 0.323; train_acc 0.891\n",
            "epoch 1, step 630: train_loss 0.581; train_acc 0.828\n",
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            "epoch 1, step 632: train_loss 0.265; train_acc 0.922\n",
            "epoch 1, step 633: train_loss 0.392; train_acc 0.891\n",
            "epoch 1, step 634: train_loss 0.396; train_acc 0.891\n",
            "epoch 1, step 635: train_loss 0.509; train_acc 0.828\n",
            "epoch 1, step 636: train_loss 0.481; train_acc 0.859\n",
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            "epoch 1, step 638: train_loss 0.319; train_acc 0.922\n",
            "epoch 1, step 639: train_loss 0.332; train_acc 0.891\n",
            "epoch 1, step 640: train_loss 0.371; train_acc 0.891\n",
            "epoch 1, step 641: train_loss 0.437; train_acc 0.859\n",
            "epoch 1, step 642: train_loss 0.496; train_acc 0.812\n",
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            "epoch 1, step 645: train_loss 0.590; train_acc 0.812\n",
            "epoch 1, step 646: train_loss 0.612; train_acc 0.781\n",
            "epoch 1, step 647: train_loss 0.386; train_acc 0.922\n",
            "epoch 1, step 648: train_loss 0.447; train_acc 0.812\n",
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            "epoch 1, step 650: train_loss 0.212; train_acc 0.922\n",
            "epoch 1, step 651: train_loss 0.616; train_acc 0.781\n",
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            "epoch 1, step 654: train_loss 0.528; train_acc 0.859\n",
            "epoch 1, step 655: train_loss 0.273; train_acc 0.891\n",
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            "epoch 1, step 657: train_loss 0.211; train_acc 0.938\n",
            "epoch 1, step 658: train_loss 0.364; train_acc 0.906\n",
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            "epoch 1, step 660: train_loss 0.465; train_acc 0.844\n",
            "epoch 1, step 661: train_loss 0.602; train_acc 0.781\n",
            "epoch 1, step 662: train_loss 0.409; train_acc 0.891\n",
            "epoch 1, step 663: train_loss 0.528; train_acc 0.812\n",
            "epoch 1, step 664: train_loss 0.505; train_acc 0.812\n",
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            "epoch 1, step 666: train_loss 0.354; train_acc 0.906\n",
            "epoch 1, step 667: train_loss 0.371; train_acc 0.875\n",
            "epoch 1, step 668: train_loss 0.255; train_acc 0.891\n",
            "epoch 1, step 669: train_loss 0.508; train_acc 0.812\n",
            "epoch 1, step 670: train_loss 0.280; train_acc 0.891\n",
            "epoch 1, step 671: train_loss 0.188; train_acc 0.953\n",
            "epoch 1, step 672: train_loss 0.270; train_acc 0.938\n",
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            "epoch 1, step 675: train_loss 0.258; train_acc 0.922\n",
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            "epoch 1, step 677: train_loss 0.334; train_acc 0.922\n",
            "epoch 1, step 678: train_loss 0.455; train_acc 0.875\n",
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            "epoch 1, step 680: train_loss 0.430; train_acc 0.859\n",
            "epoch 1, step 681: train_loss 0.330; train_acc 0.906\n",
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            "epoch 1, step 683: train_loss 0.419; train_acc 0.875\n",
            "epoch 1, step 684: train_loss 0.287; train_acc 0.891\n",
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            "epoch 1, step 686: train_loss 0.432; train_acc 0.844\n",
            "epoch 1, step 687: train_loss 0.391; train_acc 0.891\n",
            "epoch 1, step 688: train_loss 0.315; train_acc 0.891\n",
            "epoch 1, step 689: train_loss 0.303; train_acc 0.938\n",
            "epoch 1, step 690: train_loss 0.406; train_acc 0.891\n",
            "epoch 1, step 691: train_loss 0.521; train_acc 0.844\n",
            "epoch 1, step 692: train_loss 0.496; train_acc 0.844\n",
            "epoch 1, step 693: train_loss 0.336; train_acc 0.906\n",
            "epoch 1, step 694: train_loss 0.446; train_acc 0.875\n",
            "epoch 1, step 695: train_loss 0.512; train_acc 0.828\n",
            "epoch 1, step 696: train_loss 0.295; train_acc 0.891\n",
            "epoch 1, step 697: train_loss 0.194; train_acc 0.969\n",
            "epoch 1, step 698: train_loss 0.294; train_acc 0.938\n",
            "epoch 1, step 699: train_loss 0.269; train_acc 0.922\n",
            "epoch 1, step 700: train_loss 0.317; train_acc 0.906\n",
            "epoch 1, step 701: train_loss 0.411; train_acc 0.875\n",
            "epoch 1, step 702: train_loss 0.315; train_acc 0.875\n",
            "epoch 1, step 703: train_loss 0.241; train_acc 0.922\n",
            "epoch 1, step 704: train_loss 0.143; train_acc 0.984\n",
            "epoch 1, step 705: train_loss 0.443; train_acc 0.891\n",
            "epoch 1, step 706: train_loss 0.306; train_acc 0.875\n",
            "epoch 1, step 707: train_loss 0.337; train_acc 0.922\n",
            "epoch 1, step 708: train_loss 0.442; train_acc 0.875\n",
            "epoch 1, step 709: train_loss 0.345; train_acc 0.906\n",
            "epoch 1, step 710: train_loss 0.295; train_acc 0.891\n",
            "epoch 1, step 711: train_loss 0.250; train_acc 0.906\n",
            "epoch 1, step 712: train_loss 0.459; train_acc 0.859\n",
            "epoch 1, step 713: train_loss 0.302; train_acc 0.938\n",
            "epoch 1, step 714: train_loss 0.312; train_acc 0.875\n",
            "epoch 1, step 715: train_loss 0.337; train_acc 0.906\n",
            "epoch 1, step 716: train_loss 0.332; train_acc 0.891\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}