car_damage_detection_1.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/vg11072001/car_detection_damage/blob/main/car_damage_detection_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NGUQoCvMZy-I",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2a4f2b79-14dd-4188-e9b3-22f76aa578f8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install tensorflow-object-detection-api"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EOCZ9qkMg6YT",
        "outputId": "c3d6ae59-96bb-4484-c048-6a64ed2686ab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cd /content/tensorflow2/scripts/preprocessing"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XK7kb3wKhUOv",
        "outputId": "fbbc7be8-9ca8-482d-b334-392fb4a8107c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/tensorflow2/scripts/preprocessing\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python generate_tfrecord.py -x /content/tensorflow2/workspace/training_demo/images/train -l /content/tensorflow2/workspace/training_demo/annotations/labelmap.pbtxt -o /content/tensorflow2/workspace/training_demo/annotations/train.record"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EFyweE7EhT_5",
        "outputId": "50e96796-4bf8-433e-c580-bc104426a0ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Traceback (most recent call last):\n",
            "  File \"generate_tfrecord.py\", line 61, in <module>\n",
            "    label_map = label_map_util.load_labelmap(args.labels_path)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/object_detection/utils/label_map_util.py\", line 132, in load_labelmap\n",
            "    with tf.gfile.GFile(path, 'r') as fid:\n",
            "AttributeError: module 'tensorflow' has no attribute 'gfile'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python generate_tfrecord.py -x /content/tensorflow2/workspace/training_demo/images/test -l /content/tensorflow2/workspace/training_demo/annotations/labelmap.pbtxt -o /content/tensorflow2/workspace/training_demo/annotations/test.record"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "53a5cbcf-5ca7-4eee-c700-a58d48cc1b51",
        "id": "yRT5NFHvgkse"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Traceback (most recent call last):\n",
            "  File \"generate_tfrecord.py\", line 61, in <module>\n",
            "    label_map = label_map_util.load_labelmap(args.labels_path)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/object_detection/utils/label_map_util.py\", line 132, in load_labelmap\n",
            "    with tf.gfile.GFile(path, 'r') as fid:\n",
            "AttributeError: module 'tensorflow' has no attribute 'gfile'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x9DpVe3-aV2p",
        "outputId": "03500613-5dff-4c2a-f4c0-e8886113b825"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tf.Tensor(416.17804, shape=(), dtype=float32)\n"
          ]
        }
      ],
      "source": [
        "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CvNDa5vSafXj",
        "outputId": "74b60571-9761-4719-cd5f-0e061d668c40"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/tensorflow2\n"
          ]
        }
      ],
      "source": [
        "cd /content/tensorflow2/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iDXU9KKOav7K",
        "outputId": "32a19370-1b30-43af-f5c6-60cfbb6e3d80"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'models'...\n",
            "remote: Enumerating objects: 70994, done.\u001b[K\n",
            "remote: Counting objects: 100% (61/61), done.\u001b[K\n",
            "remote: Compressing objects: 100% (34/34), done.\u001b[K\n",
            "remote: Total 70994 (delta 33), reused 52 (delta 27), pack-reused 70933\u001b[K\n",
            "Receiving objects: 100% (70994/70994), 578.57 MiB | 33.06 MiB/s, done.\n",
            "Resolving deltas: 100% (50131/50131), done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/tensorflow/models.git"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IJVktRs8a5DI",
        "outputId": "d36ac206-f1f2-49cb-b6ea-9182b69fd0a2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/tensorflow2/models/research\n"
          ]
        }
      ],
      "source": [
        "cd /content/tensorflow2/models/research"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qm7nRdUJbSZD"
      },
      "outputs": [],
      "source": [
        "!protoc object_detection/protos/*.proto --python_out=."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "2XV-sySpb5mx",
        "outputId": "7731a331-f797-4f14-cd4e-6192d7d125fd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/tensorflow2/models/research'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "pwd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VoFXpIsmcE-V"
      },
      "outputs": [],
      "source": [
        "cp /content/tensorflow2/models/research/object_detection/packages/tf2/setup.py ."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uR9jUvJ4cJ67",
        "outputId": "81c9474b-0997-4669-99c9-c56af972ee91"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[33mWARNING: --use-feature=2020-resolver no longer has any effect, since it is now the default dependency resolver in pip. This will become an error in pip 21.0.\u001b[0m\n",
            "Processing /content/tensorflow2/models/research\n",
            "\u001b[33m  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n",
            "   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\u001b[0m\n",
            "Collecting avro-python3\n",
            "  Downloading avro-python3-1.10.2.tar.gz (38 kB)\n",
            "Collecting apache-beam\n",
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            "  Downloading tf_slim-1.1.0-py2.py3-none-any.whl (352 kB)\n",
            "\u001b[K     |████████████████████████████████| 352 kB 76.2 MB/s \n",
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            "  Downloading tf_models_official-2.8.0-py2.py3-none-any.whl (2.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.2 MB 48.9 MB/s \n",
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            "\u001b[?25hCollecting pyyaml<6.0,>=5.1\n",
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            "  Downloading opencv_python_headless-4.5.5.64-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (47.8 MB)\n",
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            "  Downloading tensorflow_text-2.8.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.9 MB)\n",
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            "  Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)\n",
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            "\u001b[?25hCollecting pymongo<4.0.0,>=3.8.0\n",
            "  Downloading pymongo-3.12.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (508 kB)\n",
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            "  Downloading portalocker-2.4.0-py2.py3-none-any.whl (16 kB)\n",
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            "Building wheels for collected packages: object-detection, py-cpuinfo, dill, avro-python3, seqeval\n",
            "  Building wheel for object-detection (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for object-detection: filename=object_detection-0.1-py3-none-any.whl size=1686359 sha256=39723af975daaf1150503b2075d4779fe378a55bd9a5485e2403dfacd471195a\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-rydckwry/wheels/64/3d/0f/03baf758efc36098233df6c9f8be0e1afc3326c68f3daffe70\n",
            "  Building wheel for py-cpuinfo (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for py-cpuinfo: filename=py_cpuinfo-8.0.0-py3-none-any.whl size=22257 sha256=a23a61e2fac25e5da7d8d814dd9c40cf8b495ac76cfa563addfd00c9516de996\n",
            "  Stored in directory: /root/.cache/pip/wheels/d2/f1/1f/041add21dc9c4220157f1bd2bd6afe1f1a49524c3396b94401\n",
            "  Building wheel for dill (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for dill: filename=dill-0.3.1.1-py3-none-any.whl size=78544 sha256=24a487948793cdd54e5b6ccaed9113eff9b5526025b2f8571eeb8fa3d046acac\n",
            "  Stored in directory: /root/.cache/pip/wheels/a4/61/fd/c57e374e580aa78a45ed78d5859b3a44436af17e22ca53284f\n",
            "  Building wheel for avro-python3 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for avro-python3: filename=avro_python3-1.10.2-py3-none-any.whl size=44010 sha256=7b0cc44ce189abc209535070658b573565d069800332ecfab95fe8864a0eb6e8\n",
            "  Stored in directory: /root/.cache/pip/wheels/d6/e5/b1/6b151d9b535ee50aaa6ab27d145a0104b6df02e5636f0376da\n",
            "  Building wheel for seqeval (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for seqeval: filename=seqeval-1.2.2-py3-none-any.whl size=16180 sha256=d0ffc15d743f2329e1754a679f700afdc6b329b6a9a46e67b67b7e4ad4d73143\n",
            "  Stored in directory: /root/.cache/pip/wheels/05/96/ee/7cac4e74f3b19e3158dce26a20a1c86b3533c43ec72a549fd7\n",
            "Successfully built object-detection py-cpuinfo dill avro-python3 seqeval\n",
            "Installing collected packages: requests, protobuf, portalocker, dill, tf-slim, tensorflow-text, tensorflow-model-optimization, tensorflow-addons, seqeval, sentencepiece, sacrebleu, pyyaml, pymongo, py-cpuinfo, proto-plus, orjson, opencv-python-headless, hdfs, fastavro, cloudpickle, tf-models-official, tensorflow-io, lvis, avro-python3, apache-beam, object-detection\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.23.0\n",
            "    Uninstalling requests-2.23.0:\n",
            "      Successfully uninstalled requests-2.23.0\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.17.3\n",
            "    Uninstalling protobuf-3.17.3:\n",
            "      Successfully uninstalled protobuf-3.17.3\n",
            "  Attempting uninstall: dill\n",
            "    Found existing installation: dill 0.3.4\n",
            "    Uninstalling dill-0.3.4:\n",
            "      Successfully uninstalled dill-0.3.4\n",
            "  Attempting uninstall: pyyaml\n",
            "    Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
            "  Attempting uninstall: pymongo\n",
            "    Found existing installation: pymongo 4.0.2\n",
            "    Uninstalling pymongo-4.0.2:\n",
            "      Successfully uninstalled pymongo-4.0.2\n",
            "  Attempting uninstall: cloudpickle\n",
            "    Found existing installation: cloudpickle 1.3.0\n",
            "    Uninstalling cloudpickle-1.3.0:\n",
            "      Successfully uninstalled cloudpickle-1.3.0\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "multiprocess 0.70.12.2 requires dill>=0.3.4, but you have dill 0.3.1.1 which is incompatible.\n",
            "gym 0.17.3 requires cloudpickle<1.7.0,>=1.2.0, but you have cloudpickle 2.0.0 which is incompatible.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Successfully installed apache-beam-2.37.0 avro-python3-1.10.2 cloudpickle-2.0.0 dill-0.3.1.1 fastavro-1.4.10 hdfs-2.6.0 lvis-0.5.3 object-detection-0.1 opencv-python-headless-4.5.5.64 orjson-3.6.7 portalocker-2.4.0 proto-plus-1.20.3 protobuf-3.19.4 py-cpuinfo-8.0.0 pymongo-3.12.3 pyyaml-5.4.1 requests-2.27.1 sacrebleu-2.0.0 sentencepiece-0.1.96 seqeval-1.2.2 tensorflow-addons-0.16.1 tensorflow-io-0.24.0 tensorflow-model-optimization-0.7.2 tensorflow-text-2.8.1 tf-models-official-2.8.0 tf-slim-1.1.0\n"
          ]
        }
      ],
      "source": [
        "!python -m pip install --use-feature=2020-resolver ."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bzmmYC1CeAhD",
        "outputId": "63a72d48-1638-42b1-bb56-033700607a96"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Running tests under Python 3.7.12: /usr/bin/python3\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_center_net_deepmac\n",
            "2022-03-23 16:27:37.205916: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
            "W0323 16:27:37.554414 140406263920512 model_builder.py:1100] Building experimental DeepMAC meta-arch. Some features may be omitted.\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_center_net_deepmac): 1.31s\n",
            "I0323 16:27:37.803710 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_center_net_deepmac): 1.31s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_center_net_deepmac\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_center_net_model0 (customize_head_params=True)\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_center_net_model0 (customize_head_params=True)): 0.53s\n",
            "I0323 16:27:38.337428 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_center_net_model0 (customize_head_params=True)): 0.53s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_center_net_model0 (customize_head_params=True)\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_center_net_model1 (customize_head_params=False)\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_center_net_model1 (customize_head_params=False)): 0.27s\n",
            "I0323 16:27:38.611361 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_center_net_model1 (customize_head_params=False)): 0.27s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_center_net_model1 (customize_head_params=False)\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_center_net_model_from_keypoints\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_center_net_model_from_keypoints): 0.24s\n",
            "I0323 16:27:38.853052 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_center_net_model_from_keypoints): 0.24s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_center_net_model_from_keypoints\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_center_net_model_mobilenet\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_center_net_model_mobilenet): 1.73s\n",
            "I0323 16:27:40.578671 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_center_net_model_mobilenet): 1.73s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_center_net_model_mobilenet\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_experimental_model\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_experimental_model): 0.0s\n",
            "I0323 16:27:40.579604 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_experimental_model): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_experimental_model\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature0 (True)\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature0 (True)): 0.02s\n",
            "I0323 16:27:40.601713 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature0 (True)): 0.02s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature0 (True)\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature1 (False)\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature1 (False)): 0.01s\n",
            "I0323 16:27:40.615704 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature1 (False)): 0.01s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_faster_rcnn_from_config_with_crop_feature1 (False)\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_faster_rcnn_model_from_config_with_example_miner\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_model_from_config_with_example_miner): 0.01s\n",
            "I0323 16:27:40.630631 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_model_from_config_with_example_miner): 0.01s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_faster_rcnn_model_from_config_with_example_miner\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_with_matmul\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_with_matmul): 0.1s\n",
            "I0323 16:27:40.726998 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_with_matmul): 0.1s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_with_matmul\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_without_matmul\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_without_matmul): 0.09s\n",
            "I0323 16:27:40.817967 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_without_matmul): 0.09s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_faster_rcnn_without_matmul\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_with_matmul\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_with_matmul): 0.1s\n",
            "I0323 16:27:40.916647 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_with_matmul): 0.1s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_with_matmul\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_without_matmul\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_without_matmul): 0.09s\n",
            "I0323 16:27:41.011375 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_without_matmul): 0.09s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_faster_rcnn_models_from_config_mask_rcnn_without_matmul\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_rfcn_model_from_config\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_rfcn_model_from_config): 0.09s\n",
            "I0323 16:27:41.101838 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_rfcn_model_from_config): 0.09s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_rfcn_model_from_config\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_ssd_fpn_model_from_config\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_ssd_fpn_model_from_config): 0.03s\n",
            "I0323 16:27:41.130981 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_ssd_fpn_model_from_config): 0.03s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_ssd_fpn_model_from_config\n",
            "[ RUN      ] ModelBuilderTF2Test.test_create_ssd_models_from_config\n",
            "I0323 16:27:41.317743 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b0\n",
            "I0323 16:27:41.317915 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 64\n",
            "I0323 16:27:41.318003 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 3\n",
            "I0323 16:27:41.320228 140406263920512 efficientnet_model.py:144] round_filter input=32 output=32\n",
            "I0323 16:27:41.336742 140406263920512 efficientnet_model.py:144] round_filter input=32 output=32\n",
            "I0323 16:27:41.336862 140406263920512 efficientnet_model.py:144] round_filter input=16 output=16\n",
            "I0323 16:27:41.394152 140406263920512 efficientnet_model.py:144] round_filter input=16 output=16\n",
            "I0323 16:27:41.394285 140406263920512 efficientnet_model.py:144] round_filter input=24 output=24\n",
            "I0323 16:27:41.538147 140406263920512 efficientnet_model.py:144] round_filter input=24 output=24\n",
            "I0323 16:27:41.538273 140406263920512 efficientnet_model.py:144] round_filter input=40 output=40\n",
            "I0323 16:27:41.844803 140406263920512 efficientnet_model.py:144] round_filter input=40 output=40\n",
            "I0323 16:27:41.844990 140406263920512 efficientnet_model.py:144] round_filter input=80 output=80\n",
            "I0323 16:27:42.061184 140406263920512 efficientnet_model.py:144] round_filter input=80 output=80\n",
            "I0323 16:27:42.061359 140406263920512 efficientnet_model.py:144] round_filter input=112 output=112\n",
            "I0323 16:27:42.281640 140406263920512 efficientnet_model.py:144] round_filter input=112 output=112\n",
            "I0323 16:27:42.281795 140406263920512 efficientnet_model.py:144] round_filter input=192 output=192\n",
            "I0323 16:27:42.586235 140406263920512 efficientnet_model.py:144] round_filter input=192 output=192\n",
            "I0323 16:27:42.586416 140406263920512 efficientnet_model.py:144] round_filter input=320 output=320\n",
            "I0323 16:27:42.661295 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=1280\n",
            "I0323 16:27:42.693121 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=1.0, depth_coefficient=1.0, resolution=224, dropout_rate=0.2, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "I0323 16:27:42.748098 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b1\n",
            "I0323 16:27:42.748244 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 88\n",
            "I0323 16:27:42.748327 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 4\n",
            "I0323 16:27:42.749942 140406263920512 efficientnet_model.py:144] round_filter input=32 output=32\n",
            "I0323 16:27:42.764800 140406263920512 efficientnet_model.py:144] round_filter input=32 output=32\n",
            "I0323 16:27:42.764919 140406263920512 efficientnet_model.py:144] round_filter input=16 output=16\n",
            "I0323 16:27:42.878116 140406263920512 efficientnet_model.py:144] round_filter input=16 output=16\n",
            "I0323 16:27:42.878271 140406263920512 efficientnet_model.py:144] round_filter input=24 output=24\n",
            "I0323 16:27:43.091690 140406263920512 efficientnet_model.py:144] round_filter input=24 output=24\n",
            "I0323 16:27:43.091850 140406263920512 efficientnet_model.py:144] round_filter input=40 output=40\n",
            "I0323 16:27:43.318055 140406263920512 efficientnet_model.py:144] round_filter input=40 output=40\n",
            "I0323 16:27:43.318254 140406263920512 efficientnet_model.py:144] round_filter input=80 output=80\n",
            "I0323 16:27:43.621201 140406263920512 efficientnet_model.py:144] round_filter input=80 output=80\n",
            "I0323 16:27:43.621377 140406263920512 efficientnet_model.py:144] round_filter input=112 output=112\n",
            "I0323 16:27:43.911249 140406263920512 efficientnet_model.py:144] round_filter input=112 output=112\n",
            "I0323 16:27:43.911413 140406263920512 efficientnet_model.py:144] round_filter input=192 output=192\n",
            "I0323 16:27:44.276751 140406263920512 efficientnet_model.py:144] round_filter input=192 output=192\n",
            "I0323 16:27:44.276913 140406263920512 efficientnet_model.py:144] round_filter input=320 output=320\n",
            "I0323 16:27:44.418272 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=1280\n",
            "I0323 16:27:44.446007 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=1.0, depth_coefficient=1.1, resolution=240, dropout_rate=0.2, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "I0323 16:27:44.507446 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b2\n",
            "I0323 16:27:44.507592 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 112\n",
            "I0323 16:27:44.507666 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 5\n",
            "I0323 16:27:44.509163 140406263920512 efficientnet_model.py:144] round_filter input=32 output=32\n",
            "I0323 16:27:44.523270 140406263920512 efficientnet_model.py:144] round_filter input=32 output=32\n",
            "I0323 16:27:44.523401 140406263920512 efficientnet_model.py:144] round_filter input=16 output=16\n",
            "I0323 16:27:44.638705 140406263920512 efficientnet_model.py:144] round_filter input=16 output=16\n",
            "I0323 16:27:44.638853 140406263920512 efficientnet_model.py:144] round_filter input=24 output=24\n",
            "I0323 16:27:44.858968 140406263920512 efficientnet_model.py:144] round_filter input=24 output=24\n",
            "I0323 16:27:44.859127 140406263920512 efficientnet_model.py:144] round_filter input=40 output=48\n",
            "I0323 16:27:45.068915 140406263920512 efficientnet_model.py:144] round_filter input=40 output=48\n",
            "I0323 16:27:45.069085 140406263920512 efficientnet_model.py:144] round_filter input=80 output=88\n",
            "I0323 16:27:45.372570 140406263920512 efficientnet_model.py:144] round_filter input=80 output=88\n",
            "I0323 16:27:45.372741 140406263920512 efficientnet_model.py:144] round_filter input=112 output=120\n",
            "I0323 16:27:45.825769 140406263920512 efficientnet_model.py:144] round_filter input=112 output=120\n",
            "I0323 16:27:45.825949 140406263920512 efficientnet_model.py:144] round_filter input=192 output=208\n",
            "I0323 16:27:46.185860 140406263920512 efficientnet_model.py:144] round_filter input=192 output=208\n",
            "I0323 16:27:46.186029 140406263920512 efficientnet_model.py:144] round_filter input=320 output=352\n",
            "I0323 16:27:46.336488 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=1408\n",
            "I0323 16:27:46.363371 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=1.1, depth_coefficient=1.2, resolution=260, dropout_rate=0.3, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "I0323 16:27:46.426046 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b3\n",
            "I0323 16:27:46.426177 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 160\n",
            "I0323 16:27:46.426249 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 6\n",
            "I0323 16:27:46.427763 140406263920512 efficientnet_model.py:144] round_filter input=32 output=40\n",
            "I0323 16:27:46.442700 140406263920512 efficientnet_model.py:144] round_filter input=32 output=40\n",
            "I0323 16:27:46.442810 140406263920512 efficientnet_model.py:144] round_filter input=16 output=24\n",
            "I0323 16:27:46.552236 140406263920512 efficientnet_model.py:144] round_filter input=16 output=24\n",
            "I0323 16:27:46.552382 140406263920512 efficientnet_model.py:144] round_filter input=24 output=32\n",
            "I0323 16:27:46.772550 140406263920512 efficientnet_model.py:144] round_filter input=24 output=32\n",
            "I0323 16:27:46.772697 140406263920512 efficientnet_model.py:144] round_filter input=40 output=48\n",
            "I0323 16:27:46.984349 140406263920512 efficientnet_model.py:144] round_filter input=40 output=48\n",
            "I0323 16:27:46.984528 140406263920512 efficientnet_model.py:144] round_filter input=80 output=96\n",
            "I0323 16:27:47.349589 140406263920512 efficientnet_model.py:144] round_filter input=80 output=96\n",
            "I0323 16:27:47.349759 140406263920512 efficientnet_model.py:144] round_filter input=112 output=136\n",
            "I0323 16:27:47.709215 140406263920512 efficientnet_model.py:144] round_filter input=112 output=136\n",
            "I0323 16:27:47.709387 140406263920512 efficientnet_model.py:144] round_filter input=192 output=232\n",
            "I0323 16:27:48.142911 140406263920512 efficientnet_model.py:144] round_filter input=192 output=232\n",
            "I0323 16:27:48.143078 140406263920512 efficientnet_model.py:144] round_filter input=320 output=384\n",
            "I0323 16:27:48.290741 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=1536\n",
            "I0323 16:27:48.318432 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=1.2, depth_coefficient=1.4, resolution=300, dropout_rate=0.3, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "I0323 16:27:48.383386 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b4\n",
            "I0323 16:27:48.383525 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 224\n",
            "I0323 16:27:48.383620 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 7\n",
            "I0323 16:27:48.385367 140406263920512 efficientnet_model.py:144] round_filter input=32 output=48\n",
            "I0323 16:27:48.399878 140406263920512 efficientnet_model.py:144] round_filter input=32 output=48\n",
            "I0323 16:27:48.399988 140406263920512 efficientnet_model.py:144] round_filter input=16 output=24\n",
            "I0323 16:27:48.514093 140406263920512 efficientnet_model.py:144] round_filter input=16 output=24\n",
            "I0323 16:27:48.514219 140406263920512 efficientnet_model.py:144] round_filter input=24 output=32\n",
            "I0323 16:27:48.811263 140406263920512 efficientnet_model.py:144] round_filter input=24 output=32\n",
            "I0323 16:27:48.811422 140406263920512 efficientnet_model.py:144] round_filter input=40 output=56\n",
            "I0323 16:27:49.096952 140406263920512 efficientnet_model.py:144] round_filter input=40 output=56\n",
            "I0323 16:27:49.097124 140406263920512 efficientnet_model.py:144] round_filter input=80 output=112\n",
            "I0323 16:27:49.531090 140406263920512 efficientnet_model.py:144] round_filter input=80 output=112\n",
            "I0323 16:27:49.531370 140406263920512 efficientnet_model.py:144] round_filter input=112 output=160\n",
            "I0323 16:27:49.961383 140406263920512 efficientnet_model.py:144] round_filter input=112 output=160\n",
            "I0323 16:27:49.961563 140406263920512 efficientnet_model.py:144] round_filter input=192 output=272\n",
            "I0323 16:27:50.753978 140406263920512 efficientnet_model.py:144] round_filter input=192 output=272\n",
            "I0323 16:27:50.754154 140406263920512 efficientnet_model.py:144] round_filter input=320 output=448\n",
            "I0323 16:27:50.894232 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=1792\n",
            "I0323 16:27:50.921270 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=1.4, depth_coefficient=1.8, resolution=380, dropout_rate=0.4, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "I0323 16:27:50.994511 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b5\n",
            "I0323 16:27:50.994659 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 288\n",
            "I0323 16:27:50.994733 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 7\n",
            "I0323 16:27:50.996304 140406263920512 efficientnet_model.py:144] round_filter input=32 output=48\n",
            "I0323 16:27:51.010769 140406263920512 efficientnet_model.py:144] round_filter input=32 output=48\n",
            "I0323 16:27:51.010882 140406263920512 efficientnet_model.py:144] round_filter input=16 output=24\n",
            "I0323 16:27:51.182981 140406263920512 efficientnet_model.py:144] round_filter input=16 output=24\n",
            "I0323 16:27:51.183118 140406263920512 efficientnet_model.py:144] round_filter input=24 output=40\n",
            "I0323 16:27:51.549609 140406263920512 efficientnet_model.py:144] round_filter input=24 output=40\n",
            "I0323 16:27:51.549791 140406263920512 efficientnet_model.py:144] round_filter input=40 output=64\n",
            "I0323 16:27:51.907739 140406263920512 efficientnet_model.py:144] round_filter input=40 output=64\n",
            "I0323 16:27:51.907904 140406263920512 efficientnet_model.py:144] round_filter input=80 output=128\n",
            "I0323 16:27:52.426386 140406263920512 efficientnet_model.py:144] round_filter input=80 output=128\n",
            "I0323 16:27:52.426571 140406263920512 efficientnet_model.py:144] round_filter input=112 output=176\n",
            "I0323 16:27:52.933997 140406263920512 efficientnet_model.py:144] round_filter input=112 output=176\n",
            "I0323 16:27:52.934175 140406263920512 efficientnet_model.py:144] round_filter input=192 output=304\n",
            "I0323 16:27:53.596192 140406263920512 efficientnet_model.py:144] round_filter input=192 output=304\n",
            "I0323 16:27:53.596370 140406263920512 efficientnet_model.py:144] round_filter input=320 output=512\n",
            "I0323 16:27:53.814426 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=2048\n",
            "I0323 16:27:53.844244 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=1.6, depth_coefficient=2.2, resolution=456, dropout_rate=0.4, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "I0323 16:27:53.929723 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b6\n",
            "I0323 16:27:53.929868 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 384\n",
            "I0323 16:27:53.929943 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 8\n",
            "I0323 16:27:53.931596 140406263920512 efficientnet_model.py:144] round_filter input=32 output=56\n",
            "I0323 16:27:53.946175 140406263920512 efficientnet_model.py:144] round_filter input=32 output=56\n",
            "I0323 16:27:53.946295 140406263920512 efficientnet_model.py:144] round_filter input=16 output=32\n",
            "I0323 16:27:54.117389 140406263920512 efficientnet_model.py:144] round_filter input=16 output=32\n",
            "I0323 16:27:54.117551 140406263920512 efficientnet_model.py:144] round_filter input=24 output=40\n",
            "I0323 16:27:54.559844 140406263920512 efficientnet_model.py:144] round_filter input=24 output=40\n",
            "I0323 16:27:54.560019 140406263920512 efficientnet_model.py:144] round_filter input=40 output=72\n",
            "I0323 16:27:54.998166 140406263920512 efficientnet_model.py:144] round_filter input=40 output=72\n",
            "I0323 16:27:54.998419 140406263920512 efficientnet_model.py:144] round_filter input=80 output=144\n",
            "I0323 16:27:55.815546 140406263920512 efficientnet_model.py:144] round_filter input=80 output=144\n",
            "I0323 16:27:55.815711 140406263920512 efficientnet_model.py:144] round_filter input=112 output=200\n",
            "I0323 16:27:56.389502 140406263920512 efficientnet_model.py:144] round_filter input=112 output=200\n",
            "I0323 16:27:56.389663 140406263920512 efficientnet_model.py:144] round_filter input=192 output=344\n",
            "I0323 16:27:57.189833 140406263920512 efficientnet_model.py:144] round_filter input=192 output=344\n",
            "I0323 16:27:57.190007 140406263920512 efficientnet_model.py:144] round_filter input=320 output=576\n",
            "I0323 16:27:57.402337 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=2304\n",
            "I0323 16:27:57.429126 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=1.8, depth_coefficient=2.6, resolution=528, dropout_rate=0.5, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "I0323 16:27:57.539894 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:146] EfficientDet EfficientNet backbone version: efficientnet-b7\n",
            "I0323 16:27:57.540047 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num filters: 384\n",
            "I0323 16:27:57.540117 140406263920512 ssd_efficientnet_bifpn_feature_extractor.py:149] EfficientDet BiFPN num iterations: 8\n",
            "I0323 16:27:57.541735 140406263920512 efficientnet_model.py:144] round_filter input=32 output=64\n",
            "I0323 16:27:57.556584 140406263920512 efficientnet_model.py:144] round_filter input=32 output=64\n",
            "I0323 16:27:57.556694 140406263920512 efficientnet_model.py:144] round_filter input=16 output=32\n",
            "I0323 16:27:57.788686 140406263920512 efficientnet_model.py:144] round_filter input=16 output=32\n",
            "I0323 16:27:57.788848 140406263920512 efficientnet_model.py:144] round_filter input=24 output=48\n",
            "I0323 16:27:58.295907 140406263920512 efficientnet_model.py:144] round_filter input=24 output=48\n",
            "I0323 16:27:58.296094 140406263920512 efficientnet_model.py:144] round_filter input=40 output=80\n",
            "I0323 16:27:58.808032 140406263920512 efficientnet_model.py:144] round_filter input=40 output=80\n",
            "I0323 16:27:58.808202 140406263920512 efficientnet_model.py:144] round_filter input=80 output=160\n",
            "I0323 16:27:59.534457 140406263920512 efficientnet_model.py:144] round_filter input=80 output=160\n",
            "I0323 16:27:59.534636 140406263920512 efficientnet_model.py:144] round_filter input=112 output=224\n",
            "I0323 16:28:00.486490 140406263920512 efficientnet_model.py:144] round_filter input=112 output=224\n",
            "I0323 16:28:00.486678 140406263920512 efficientnet_model.py:144] round_filter input=192 output=384\n",
            "I0323 16:28:01.420738 140406263920512 efficientnet_model.py:144] round_filter input=192 output=384\n",
            "I0323 16:28:01.420911 140406263920512 efficientnet_model.py:144] round_filter input=320 output=640\n",
            "I0323 16:28:01.712290 140406263920512 efficientnet_model.py:144] round_filter input=1280 output=2560\n",
            "I0323 16:28:01.748610 140406263920512 efficientnet_model.py:454] Building model efficientnet with params ModelConfig(width_coefficient=2.0, depth_coefficient=3.1, resolution=600, dropout_rate=0.5, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_create_ssd_models_from_config): 20.73s\n",
            "I0323 16:28:01.860286 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_create_ssd_models_from_config): 20.73s\n",
            "[       OK ] ModelBuilderTF2Test.test_create_ssd_models_from_config\n",
            "[ RUN      ] ModelBuilderTF2Test.test_invalid_faster_rcnn_batchnorm_update\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_invalid_faster_rcnn_batchnorm_update): 0.0s\n",
            "I0323 16:28:01.866607 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_invalid_faster_rcnn_batchnorm_update): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_invalid_faster_rcnn_batchnorm_update\n",
            "[ RUN      ] ModelBuilderTF2Test.test_invalid_first_stage_nms_iou_threshold\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_invalid_first_stage_nms_iou_threshold): 0.0s\n",
            "I0323 16:28:01.868198 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_invalid_first_stage_nms_iou_threshold): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_invalid_first_stage_nms_iou_threshold\n",
            "[ RUN      ] ModelBuilderTF2Test.test_invalid_model_config_proto\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_invalid_model_config_proto): 0.0s\n",
            "I0323 16:28:01.868704 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_invalid_model_config_proto): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_invalid_model_config_proto\n",
            "[ RUN      ] ModelBuilderTF2Test.test_invalid_second_stage_batch_size\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_invalid_second_stage_batch_size): 0.0s\n",
            "I0323 16:28:01.870130 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_invalid_second_stage_batch_size): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_invalid_second_stage_batch_size\n",
            "[ RUN      ] ModelBuilderTF2Test.test_session\n",
            "[  SKIPPED ] ModelBuilderTF2Test.test_session\n",
            "[ RUN      ] ModelBuilderTF2Test.test_unknown_faster_rcnn_feature_extractor\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_unknown_faster_rcnn_feature_extractor): 0.0s\n",
            "I0323 16:28:01.871443 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_unknown_faster_rcnn_feature_extractor): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_unknown_faster_rcnn_feature_extractor\n",
            "[ RUN      ] ModelBuilderTF2Test.test_unknown_meta_architecture\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_unknown_meta_architecture): 0.0s\n",
            "I0323 16:28:01.871878 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_unknown_meta_architecture): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_unknown_meta_architecture\n",
            "[ RUN      ] ModelBuilderTF2Test.test_unknown_ssd_feature_extractor\n",
            "INFO:tensorflow:time(__main__.ModelBuilderTF2Test.test_unknown_ssd_feature_extractor): 0.0s\n",
            "I0323 16:28:01.872845 140406263920512 test_util.py:2374] time(__main__.ModelBuilderTF2Test.test_unknown_ssd_feature_extractor): 0.0s\n",
            "[       OK ] ModelBuilderTF2Test.test_unknown_ssd_feature_extractor\n",
            "----------------------------------------------------------------------\n",
            "Ran 24 tests in 25.379s\n",
            "\n",
            "OK (skipped=1)\n"
          ]
        }
      ],
      "source": [
        "!python /content/tensorflow2/models/research/object_detection/builders/model_builder_tf2_test.py"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VxRsbQU4eoGV",
        "outputId": "87dd4626-cbc7-44bb-e0a6-de970708ac95"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/tensorflow2/workspace/training_demo\n"
          ]
        }
      ],
      "source": [
        "cd /content/tensorflow2/workspace/training_demo/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WBoFoy4teu2Y",
        "outputId": "b6f491c0-8b87-4a2e-80e2-f528ecf15f76"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2022-03-23 16:28:36.642362: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
            "INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',)\n",
            "I0323 16:28:36.648946 140461325010816 mirrored_strategy.py:374] Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',)\n",
            "INFO:tensorflow:Maybe overwriting train_steps: None\n",
            "I0323 16:28:36.658324 140461325010816 config_util.py:552] Maybe overwriting train_steps: None\n",
            "INFO:tensorflow:Maybe overwriting use_bfloat16: False\n",
            "I0323 16:28:36.658538 140461325010816 config_util.py:552] Maybe overwriting use_bfloat16: False\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:564: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "rename to distribute_datasets_from_function\n",
            "W0323 16:28:36.706389 140461325010816 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:564: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "rename to distribute_datasets_from_function\n",
            "INFO:tensorflow:Reading unweighted datasets: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "I0323 16:28:36.718415 140461325010816 dataset_builder.py:163] Reading unweighted datasets: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "INFO:tensorflow:Reading record datasets for input file: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "I0323 16:28:36.718643 140461325010816 dataset_builder.py:80] Reading record datasets for input file: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "INFO:tensorflow:Number of filenames to read: 1\n",
            "I0323 16:28:36.718747 140461325010816 dataset_builder.py:81] Number of filenames to read: 1\n",
            "WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.\n",
            "W0323 16:28:36.718831 140461325010816 dataset_builder.py:88] num_readers has been reduced to 1 to match input file shards.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
            "W0323 16:28:36.724380 140461325010816 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.map()\n",
            "W0323 16:28:36.763183 140461325010816 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.map()\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
            "W0323 16:28:49.153488 140461325010816 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "`seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead.\n",
            "W0323 16:28:52.128661 140461325010816 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "`seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "W0323 16:28:53.774954 140461325010816 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "/usr/local/lib/python3.7/dist-packages/keras/backend.py:450: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
            "  warnings.warn('`tf.keras.backend.set_learning_phase` is deprecated and '\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.113451 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.114699 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.116732 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.117612 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.119661 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.120532 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.122882 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.123810 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.125463 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "I0323 16:29:28.126332 140461325010816 cross_device_ops.py:618] Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',).\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/deprecation.py:616: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with dtype is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use fn_output_signature instead\n",
            "W0323 16:29:29.091109 140456174737152 deprecation.py:547] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/deprecation.py:616: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with dtype is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use fn_output_signature instead\n",
            "INFO:tensorflow:Step 100 per-step time 0.907s\n",
            "I0323 16:30:59.526313 140461325010816 model_lib_v2.py:707] Step 100 per-step time 0.907s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 4.027021,\n",
            " 'Loss/localization_loss': 0.641832,\n",
            " 'Loss/regularization_loss': 2.500721,\n",
            " 'Loss/total_loss': 7.169574,\n",
            " 'learning_rate': 0.014666351}\n",
            "I0323 16:30:59.526675 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 4.027021,\n",
            " 'Loss/localization_loss': 0.641832,\n",
            " 'Loss/regularization_loss': 2.500721,\n",
            " 'Loss/total_loss': 7.169574,\n",
            " 'learning_rate': 0.014666351}\n",
            "INFO:tensorflow:Step 200 per-step time 0.572s\n",
            "I0323 16:31:56.531914 140461325010816 model_lib_v2.py:707] Step 200 per-step time 0.572s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.549273,\n",
            " 'Loss/localization_loss': 0.4633955,\n",
            " 'Loss/regularization_loss': 2.4773233,\n",
            " 'Loss/total_loss': 3.4899917,\n",
            " 'learning_rate': 0.0159997}\n",
            "I0323 16:31:56.532291 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.549273,\n",
            " 'Loss/localization_loss': 0.4633955,\n",
            " 'Loss/regularization_loss': 2.4773233,\n",
            " 'Loss/total_loss': 3.4899917,\n",
            " 'learning_rate': 0.0159997}\n",
            "INFO:tensorflow:Step 300 per-step time 0.576s\n",
            "I0323 16:32:54.140021 140461325010816 model_lib_v2.py:707] Step 300 per-step time 0.576s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5230462,\n",
            " 'Loss/localization_loss': 0.57494164,\n",
            " 'Loss/regularization_loss': 2.444193,\n",
            " 'Loss/total_loss': 3.5421808,\n",
            " 'learning_rate': 0.01733305}\n",
            "I0323 16:32:54.140329 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5230462,\n",
            " 'Loss/localization_loss': 0.57494164,\n",
            " 'Loss/regularization_loss': 2.444193,\n",
            " 'Loss/total_loss': 3.5421808,\n",
            " 'learning_rate': 0.01733305}\n",
            "INFO:tensorflow:Step 400 per-step time 0.575s\n",
            "I0323 16:33:51.661052 140461325010816 model_lib_v2.py:707] Step 400 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.72804826,\n",
            " 'Loss/localization_loss': 0.64943826,\n",
            " 'Loss/regularization_loss': 2.4098604,\n",
            " 'Loss/total_loss': 3.7873468,\n",
            " 'learning_rate': 0.0186664}\n",
            "I0323 16:33:51.661452 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.72804826,\n",
            " 'Loss/localization_loss': 0.64943826,\n",
            " 'Loss/regularization_loss': 2.4098604,\n",
            " 'Loss/total_loss': 3.7873468,\n",
            " 'learning_rate': 0.0186664}\n",
            "INFO:tensorflow:Step 500 per-step time 0.577s\n",
            "I0323 16:34:49.311521 140461325010816 model_lib_v2.py:707] Step 500 per-step time 0.577s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.527122,\n",
            " 'Loss/localization_loss': 0.5184973,\n",
            " 'Loss/regularization_loss': 2.373681,\n",
            " 'Loss/total_loss': 3.4193003,\n",
            " 'learning_rate': 0.01999975}\n",
            "I0323 16:34:49.311849 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.527122,\n",
            " 'Loss/localization_loss': 0.5184973,\n",
            " 'Loss/regularization_loss': 2.373681,\n",
            " 'Loss/total_loss': 3.4193003,\n",
            " 'learning_rate': 0.01999975}\n",
            "INFO:tensorflow:Step 600 per-step time 0.575s\n",
            "I0323 16:35:46.821607 140461325010816 model_lib_v2.py:707] Step 600 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 1.0467918,\n",
            " 'Loss/localization_loss': 0.5588555,\n",
            " 'Loss/regularization_loss': 2.3367927,\n",
            " 'Loss/total_loss': 3.94244,\n",
            " 'learning_rate': 0.0213331}\n",
            "I0323 16:35:46.821961 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 1.0467918,\n",
            " 'Loss/localization_loss': 0.5588555,\n",
            " 'Loss/regularization_loss': 2.3367927,\n",
            " 'Loss/total_loss': 3.94244,\n",
            " 'learning_rate': 0.0213331}\n",
            "INFO:tensorflow:Step 700 per-step time 0.574s\n",
            "I0323 16:36:44.264243 140461325010816 model_lib_v2.py:707] Step 700 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.7591168,\n",
            " 'Loss/localization_loss': 0.73947823,\n",
            " 'Loss/regularization_loss': 2.2969568,\n",
            " 'Loss/total_loss': 3.7955518,\n",
            " 'learning_rate': 0.02266645}\n",
            "I0323 16:36:44.264594 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.7591168,\n",
            " 'Loss/localization_loss': 0.73947823,\n",
            " 'Loss/regularization_loss': 2.2969568,\n",
            " 'Loss/total_loss': 3.7955518,\n",
            " 'learning_rate': 0.02266645}\n",
            "INFO:tensorflow:Step 800 per-step time 0.576s\n",
            "I0323 16:37:41.895790 140461325010816 model_lib_v2.py:707] Step 800 per-step time 0.576s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.45005667,\n",
            " 'Loss/localization_loss': 0.5633712,\n",
            " 'Loss/regularization_loss': 2.2552536,\n",
            " 'Loss/total_loss': 3.2686815,\n",
            " 'learning_rate': 0.023999799}\n",
            "I0323 16:37:41.896133 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.45005667,\n",
            " 'Loss/localization_loss': 0.5633712,\n",
            " 'Loss/regularization_loss': 2.2552536,\n",
            " 'Loss/total_loss': 3.2686815,\n",
            " 'learning_rate': 0.023999799}\n",
            "INFO:tensorflow:Step 900 per-step time 0.575s\n",
            "I0323 16:38:39.416522 140461325010816 model_lib_v2.py:707] Step 900 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.8264741,\n",
            " 'Loss/localization_loss': 0.57929146,\n",
            " 'Loss/regularization_loss': 2.2120125,\n",
            " 'Loss/total_loss': 3.617778,\n",
            " 'learning_rate': 0.025333151}\n",
            "I0323 16:38:39.416857 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.8264741,\n",
            " 'Loss/localization_loss': 0.57929146,\n",
            " 'Loss/regularization_loss': 2.2120125,\n",
            " 'Loss/total_loss': 3.617778,\n",
            " 'learning_rate': 0.025333151}\n",
            "INFO:tensorflow:Step 1000 per-step time 0.576s\n",
            "I0323 16:39:36.997542 140461325010816 model_lib_v2.py:707] Step 1000 per-step time 0.576s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.4008668,\n",
            " 'Loss/localization_loss': 0.73514694,\n",
            " 'Loss/regularization_loss': 2.1680765,\n",
            " 'Loss/total_loss': 3.3040903,\n",
            " 'learning_rate': 0.0266665}\n",
            "I0323 16:39:36.997875 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.4008668,\n",
            " 'Loss/localization_loss': 0.73514694,\n",
            " 'Loss/regularization_loss': 2.1680765,\n",
            " 'Loss/total_loss': 3.3040903,\n",
            " 'learning_rate': 0.0266665}\n",
            "INFO:tensorflow:Step 1100 per-step time 0.590s\n",
            "I0323 16:40:35.988159 140461325010816 model_lib_v2.py:707] Step 1100 per-step time 0.590s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.7271468,\n",
            " 'Loss/localization_loss': 0.46504468,\n",
            " 'Loss/regularization_loss': 2.123054,\n",
            " 'Loss/total_loss': 3.3152456,\n",
            " 'learning_rate': 0.02799985}\n",
            "I0323 16:40:35.988463 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.7271468,\n",
            " 'Loss/localization_loss': 0.46504468,\n",
            " 'Loss/regularization_loss': 2.123054,\n",
            " 'Loss/total_loss': 3.3152456,\n",
            " 'learning_rate': 0.02799985}\n",
            "INFO:tensorflow:Step 1200 per-step time 0.577s\n",
            "I0323 16:41:33.639859 140461325010816 model_lib_v2.py:707] Step 1200 per-step time 0.577s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.7726782,\n",
            " 'Loss/localization_loss': 0.688225,\n",
            " 'Loss/regularization_loss': 2.0758162,\n",
            " 'Loss/total_loss': 3.5367193,\n",
            " 'learning_rate': 0.0293332}\n",
            "I0323 16:41:33.640230 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.7726782,\n",
            " 'Loss/localization_loss': 0.688225,\n",
            " 'Loss/regularization_loss': 2.0758162,\n",
            " 'Loss/total_loss': 3.5367193,\n",
            " 'learning_rate': 0.0293332}\n",
            "INFO:tensorflow:Step 1300 per-step time 0.575s\n",
            "I0323 16:42:31.163481 140461325010816 model_lib_v2.py:707] Step 1300 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.51653045,\n",
            " 'Loss/localization_loss': 0.4267181,\n",
            " 'Loss/regularization_loss': 2.0275588,\n",
            " 'Loss/total_loss': 2.9708073,\n",
            " 'learning_rate': 0.03066655}\n",
            "I0323 16:42:31.163794 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.51653045,\n",
            " 'Loss/localization_loss': 0.4267181,\n",
            " 'Loss/regularization_loss': 2.0275588,\n",
            " 'Loss/total_loss': 2.9708073,\n",
            " 'learning_rate': 0.03066655}\n",
            "INFO:tensorflow:Step 1400 per-step time 0.576s\n",
            "I0323 16:43:28.735229 140461325010816 model_lib_v2.py:707] Step 1400 per-step time 0.576s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.33608013,\n",
            " 'Loss/localization_loss': 0.42207518,\n",
            " 'Loss/regularization_loss': 1.9784894,\n",
            " 'Loss/total_loss': 2.7366447,\n",
            " 'learning_rate': 0.0319999}\n",
            "I0323 16:43:28.735577 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.33608013,\n",
            " 'Loss/localization_loss': 0.42207518,\n",
            " 'Loss/regularization_loss': 1.9784894,\n",
            " 'Loss/total_loss': 2.7366447,\n",
            " 'learning_rate': 0.0319999}\n",
            "INFO:tensorflow:Step 1500 per-step time 0.575s\n",
            "I0323 16:44:26.205584 140461325010816 model_lib_v2.py:707] Step 1500 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.49415296,\n",
            " 'Loss/localization_loss': 0.5349022,\n",
            " 'Loss/regularization_loss': 1.9284172,\n",
            " 'Loss/total_loss': 2.9574723,\n",
            " 'learning_rate': 0.03333325}\n",
            "I0323 16:44:26.205895 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.49415296,\n",
            " 'Loss/localization_loss': 0.5349022,\n",
            " 'Loss/regularization_loss': 1.9284172,\n",
            " 'Loss/total_loss': 2.9574723,\n",
            " 'learning_rate': 0.03333325}\n",
            "INFO:tensorflow:Step 1600 per-step time 0.574s\n",
            "I0323 16:45:23.552126 140461325010816 model_lib_v2.py:707] Step 1600 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.46928164,\n",
            " 'Loss/localization_loss': 0.55296147,\n",
            " 'Loss/regularization_loss': 1.8775635,\n",
            " 'Loss/total_loss': 2.8998065,\n",
            " 'learning_rate': 0.034666598}\n",
            "I0323 16:45:23.552512 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.46928164,\n",
            " 'Loss/localization_loss': 0.55296147,\n",
            " 'Loss/regularization_loss': 1.8775635,\n",
            " 'Loss/total_loss': 2.8998065,\n",
            " 'learning_rate': 0.034666598}\n",
            "INFO:tensorflow:Step 1700 per-step time 0.576s\n",
            "I0323 16:46:21.171202 140461325010816 model_lib_v2.py:707] Step 1700 per-step time 0.576s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.7571594,\n",
            " 'Loss/localization_loss': 0.6568582,\n",
            " 'Loss/regularization_loss': 1.8262657,\n",
            " 'Loss/total_loss': 3.2402835,\n",
            " 'learning_rate': 0.03599995}\n",
            "I0323 16:46:21.171615 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.7571594,\n",
            " 'Loss/localization_loss': 0.6568582,\n",
            " 'Loss/regularization_loss': 1.8262657,\n",
            " 'Loss/total_loss': 3.2402835,\n",
            " 'learning_rate': 0.03599995}\n",
            "INFO:tensorflow:Step 1800 per-step time 0.575s\n",
            "I0323 16:47:18.680803 140461325010816 model_lib_v2.py:707] Step 1800 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.48144844,\n",
            " 'Loss/localization_loss': 0.55270535,\n",
            " 'Loss/regularization_loss': 1.7750198,\n",
            " 'Loss/total_loss': 2.8091736,\n",
            " 'learning_rate': 0.037333302}\n",
            "I0323 16:47:18.681109 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.48144844,\n",
            " 'Loss/localization_loss': 0.55270535,\n",
            " 'Loss/regularization_loss': 1.7750198,\n",
            " 'Loss/total_loss': 2.8091736,\n",
            " 'learning_rate': 0.037333302}\n",
            "INFO:tensorflow:Step 1900 per-step time 0.574s\n",
            "I0323 16:48:16.108416 140461325010816 model_lib_v2.py:707] Step 1900 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.673305,\n",
            " 'Loss/localization_loss': 0.6371833,\n",
            " 'Loss/regularization_loss': 1.7228335,\n",
            " 'Loss/total_loss': 3.0333219,\n",
            " 'learning_rate': 0.03866665}\n",
            "I0323 16:48:16.108772 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.673305,\n",
            " 'Loss/localization_loss': 0.6371833,\n",
            " 'Loss/regularization_loss': 1.7228335,\n",
            " 'Loss/total_loss': 3.0333219,\n",
            " 'learning_rate': 0.03866665}\n",
            "INFO:tensorflow:Step 2000 per-step time 0.575s\n",
            "I0323 16:49:13.570396 140461325010816 model_lib_v2.py:707] Step 2000 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5768836,\n",
            " 'Loss/localization_loss': 0.6206904,\n",
            " 'Loss/regularization_loss': 1.6705538,\n",
            " 'Loss/total_loss': 2.8681278,\n",
            " 'learning_rate': 0.04}\n",
            "I0323 16:49:13.570713 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5768836,\n",
            " 'Loss/localization_loss': 0.6206904,\n",
            " 'Loss/regularization_loss': 1.6705538,\n",
            " 'Loss/total_loss': 2.8681278,\n",
            " 'learning_rate': 0.04}\n",
            "INFO:tensorflow:Step 2100 per-step time 0.584s\n",
            "I0323 16:50:11.960487 140461325010816 model_lib_v2.py:707] Step 2100 per-step time 0.584s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.53839844,\n",
            " 'Loss/localization_loss': 0.5718863,\n",
            " 'Loss/regularization_loss': 1.6190158,\n",
            " 'Loss/total_loss': 2.7293005,\n",
            " 'learning_rate': 0.039984576}\n",
            "I0323 16:50:11.960847 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.53839844,\n",
            " 'Loss/localization_loss': 0.5718863,\n",
            " 'Loss/regularization_loss': 1.6190158,\n",
            " 'Loss/total_loss': 2.7293005,\n",
            " 'learning_rate': 0.039984576}\n",
            "INFO:tensorflow:Step 2200 per-step time 0.575s\n",
            "I0323 16:51:09.438485 140461325010816 model_lib_v2.py:707] Step 2200 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.55642694,\n",
            " 'Loss/localization_loss': 0.60414726,\n",
            " 'Loss/regularization_loss': 1.5688435,\n",
            " 'Loss/total_loss': 2.7294178,\n",
            " 'learning_rate': 0.039938346}\n",
            "I0323 16:51:09.438803 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.55642694,\n",
            " 'Loss/localization_loss': 0.60414726,\n",
            " 'Loss/regularization_loss': 1.5688435,\n",
            " 'Loss/total_loss': 2.7294178,\n",
            " 'learning_rate': 0.039938346}\n",
            "INFO:tensorflow:Step 2300 per-step time 0.575s\n",
            "I0323 16:52:06.908059 140461325010816 model_lib_v2.py:707] Step 2300 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.49459684,\n",
            " 'Loss/localization_loss': 0.5426147,\n",
            " 'Loss/regularization_loss': 1.5209638,\n",
            " 'Loss/total_loss': 2.5581753,\n",
            " 'learning_rate': 0.03986137}\n",
            "I0323 16:52:06.908380 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.49459684,\n",
            " 'Loss/localization_loss': 0.5426147,\n",
            " 'Loss/regularization_loss': 1.5209638,\n",
            " 'Loss/total_loss': 2.5581753,\n",
            " 'learning_rate': 0.03986137}\n",
            "INFO:tensorflow:Step 2400 per-step time 0.574s\n",
            "I0323 16:53:04.283887 140461325010816 model_lib_v2.py:707] Step 2400 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.454242,\n",
            " 'Loss/localization_loss': 0.4948447,\n",
            " 'Loss/regularization_loss': 1.4744143,\n",
            " 'Loss/total_loss': 2.423501,\n",
            " 'learning_rate': 0.039753765}\n",
            "I0323 16:53:04.284237 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.454242,\n",
            " 'Loss/localization_loss': 0.4948447,\n",
            " 'Loss/regularization_loss': 1.4744143,\n",
            " 'Loss/total_loss': 2.423501,\n",
            " 'learning_rate': 0.039753765}\n",
            "INFO:tensorflow:Step 2500 per-step time 0.575s\n",
            "I0323 16:54:01.733945 140461325010816 model_lib_v2.py:707] Step 2500 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.4099972,\n",
            " 'Loss/localization_loss': 0.53036183,\n",
            " 'Loss/regularization_loss': 1.4311191,\n",
            " 'Loss/total_loss': 2.371478,\n",
            " 'learning_rate': 0.039615706}\n",
            "I0323 16:54:01.734255 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.4099972,\n",
            " 'Loss/localization_loss': 0.53036183,\n",
            " 'Loss/regularization_loss': 1.4311191,\n",
            " 'Loss/total_loss': 2.371478,\n",
            " 'learning_rate': 0.039615706}\n",
            "INFO:tensorflow:Step 2600 per-step time 0.574s\n",
            "I0323 16:54:59.181544 140461325010816 model_lib_v2.py:707] Step 2600 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.64189917,\n",
            " 'Loss/localization_loss': 0.6629648,\n",
            " 'Loss/regularization_loss': 1.3877962,\n",
            " 'Loss/total_loss': 2.69266,\n",
            " 'learning_rate': 0.039447397}\n",
            "I0323 16:54:59.181872 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.64189917,\n",
            " 'Loss/localization_loss': 0.6629648,\n",
            " 'Loss/regularization_loss': 1.3877962,\n",
            " 'Loss/total_loss': 2.69266,\n",
            " 'learning_rate': 0.039447397}\n",
            "INFO:tensorflow:Step 2700 per-step time 0.576s\n",
            "I0323 16:55:56.786707 140461325010816 model_lib_v2.py:707] Step 2700 per-step time 0.576s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5385445,\n",
            " 'Loss/localization_loss': 0.52527803,\n",
            " 'Loss/regularization_loss': 1.3456681,\n",
            " 'Loss/total_loss': 2.4094906,\n",
            " 'learning_rate': 0.039249104}\n",
            "I0323 16:55:56.787034 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5385445,\n",
            " 'Loss/localization_loss': 0.52527803,\n",
            " 'Loss/regularization_loss': 1.3456681,\n",
            " 'Loss/total_loss': 2.4094906,\n",
            " 'learning_rate': 0.039249104}\n",
            "INFO:tensorflow:Step 2800 per-step time 0.574s\n",
            "I0323 16:56:54.164487 140461325010816 model_lib_v2.py:707] Step 2800 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5264477,\n",
            " 'Loss/localization_loss': 0.4764397,\n",
            " 'Loss/regularization_loss': 1.3051828,\n",
            " 'Loss/total_loss': 2.3080702,\n",
            " 'learning_rate': 0.039021127}\n",
            "I0323 16:56:54.164784 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5264477,\n",
            " 'Loss/localization_loss': 0.4764397,\n",
            " 'Loss/regularization_loss': 1.3051828,\n",
            " 'Loss/total_loss': 2.3080702,\n",
            " 'learning_rate': 0.039021127}\n",
            "INFO:tensorflow:Step 2900 per-step time 0.573s\n",
            "I0323 16:57:51.453265 140461325010816 model_lib_v2.py:707] Step 2900 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.56991506,\n",
            " 'Loss/localization_loss': 0.54605275,\n",
            " 'Loss/regularization_loss': 1.2659503,\n",
            " 'Loss/total_loss': 2.381918,\n",
            " 'learning_rate': 0.03876383}\n",
            "I0323 16:57:51.453599 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.56991506,\n",
            " 'Loss/localization_loss': 0.54605275,\n",
            " 'Loss/regularization_loss': 1.2659503,\n",
            " 'Loss/total_loss': 2.381918,\n",
            " 'learning_rate': 0.03876383}\n",
            "INFO:tensorflow:Step 3000 per-step time 0.574s\n",
            "I0323 16:58:48.819274 140461325010816 model_lib_v2.py:707] Step 3000 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.7732565,\n",
            " 'Loss/localization_loss': 0.7302871,\n",
            " 'Loss/regularization_loss': 1.2280893,\n",
            " 'Loss/total_loss': 2.731633,\n",
            " 'learning_rate': 0.038477592}\n",
            "I0323 16:58:48.819581 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.7732565,\n",
            " 'Loss/localization_loss': 0.7302871,\n",
            " 'Loss/regularization_loss': 1.2280893,\n",
            " 'Loss/total_loss': 2.731633,\n",
            " 'learning_rate': 0.038477592}\n",
            "INFO:tensorflow:Step 3100 per-step time 0.585s\n",
            "I0323 16:59:47.295929 140461325010816 model_lib_v2.py:707] Step 3100 per-step time 0.585s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.47020096,\n",
            " 'Loss/localization_loss': 0.6129279,\n",
            " 'Loss/regularization_loss': 1.1918164,\n",
            " 'Loss/total_loss': 2.2749453,\n",
            " 'learning_rate': 0.03816286}\n",
            "I0323 16:59:47.296267 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.47020096,\n",
            " 'Loss/localization_loss': 0.6129279,\n",
            " 'Loss/regularization_loss': 1.1918164,\n",
            " 'Loss/total_loss': 2.2749453,\n",
            " 'learning_rate': 0.03816286}\n",
            "INFO:tensorflow:Step 3200 per-step time 0.574s\n",
            "I0323 17:00:44.709274 140461325010816 model_lib_v2.py:707] Step 3200 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.52814764,\n",
            " 'Loss/localization_loss': 0.52814317,\n",
            " 'Loss/regularization_loss': 1.1570865,\n",
            " 'Loss/total_loss': 2.2133775,\n",
            " 'learning_rate': 0.037820127}\n",
            "I0323 17:00:44.709585 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.52814764,\n",
            " 'Loss/localization_loss': 0.52814317,\n",
            " 'Loss/regularization_loss': 1.1570865,\n",
            " 'Loss/total_loss': 2.2133775,\n",
            " 'learning_rate': 0.037820127}\n",
            "INFO:tensorflow:Step 3300 per-step time 0.574s\n",
            "I0323 17:01:42.148742 140461325010816 model_lib_v2.py:707] Step 3300 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5789554,\n",
            " 'Loss/localization_loss': 0.6496006,\n",
            " 'Loss/regularization_loss': 1.1236854,\n",
            " 'Loss/total_loss': 2.3522415,\n",
            " 'learning_rate': 0.03744992}\n",
            "I0323 17:01:42.149072 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5789554,\n",
            " 'Loss/localization_loss': 0.6496006,\n",
            " 'Loss/regularization_loss': 1.1236854,\n",
            " 'Loss/total_loss': 2.3522415,\n",
            " 'learning_rate': 0.03744992}\n",
            "INFO:tensorflow:Step 3400 per-step time 0.574s\n",
            "I0323 17:02:39.527338 140461325010816 model_lib_v2.py:707] Step 3400 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5656712,\n",
            " 'Loss/localization_loss': 0.6477284,\n",
            " 'Loss/regularization_loss': 1.0915432,\n",
            " 'Loss/total_loss': 2.3049428,\n",
            " 'learning_rate': 0.037052803}\n",
            "I0323 17:02:39.527642 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5656712,\n",
            " 'Loss/localization_loss': 0.6477284,\n",
            " 'Loss/regularization_loss': 1.0915432,\n",
            " 'Loss/total_loss': 2.3049428,\n",
            " 'learning_rate': 0.037052803}\n",
            "INFO:tensorflow:Step 3500 per-step time 0.574s\n",
            "I0323 17:03:36.886397 140461325010816 model_lib_v2.py:707] Step 3500 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.49699995,\n",
            " 'Loss/localization_loss': 0.52378607,\n",
            " 'Loss/regularization_loss': 1.0605948,\n",
            " 'Loss/total_loss': 2.0813808,\n",
            " 'learning_rate': 0.036629394}\n",
            "I0323 17:03:36.886732 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.49699995,\n",
            " 'Loss/localization_loss': 0.52378607,\n",
            " 'Loss/regularization_loss': 1.0605948,\n",
            " 'Loss/total_loss': 2.0813808,\n",
            " 'learning_rate': 0.036629394}\n",
            "INFO:tensorflow:Step 3600 per-step time 0.574s\n",
            "I0323 17:04:34.286526 140461325010816 model_lib_v2.py:707] Step 3600 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5176985,\n",
            " 'Loss/localization_loss': 0.60904247,\n",
            " 'Loss/regularization_loss': 1.030771,\n",
            " 'Loss/total_loss': 2.157512,\n",
            " 'learning_rate': 0.03618034}\n",
            "I0323 17:04:34.286834 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5176985,\n",
            " 'Loss/localization_loss': 0.60904247,\n",
            " 'Loss/regularization_loss': 1.030771,\n",
            " 'Loss/total_loss': 2.157512,\n",
            " 'learning_rate': 0.03618034}\n",
            "INFO:tensorflow:Step 3700 per-step time 0.573s\n",
            "I0323 17:05:31.574269 140461325010816 model_lib_v2.py:707] Step 3700 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5289613,\n",
            " 'Loss/localization_loss': 0.64523953,\n",
            " 'Loss/regularization_loss': 1.0023017,\n",
            " 'Loss/total_loss': 2.1765025,\n",
            " 'learning_rate': 0.035706338}\n",
            "I0323 17:05:31.574581 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5289613,\n",
            " 'Loss/localization_loss': 0.64523953,\n",
            " 'Loss/regularization_loss': 1.0023017,\n",
            " 'Loss/total_loss': 2.1765025,\n",
            " 'learning_rate': 0.035706338}\n",
            "INFO:tensorflow:Step 3800 per-step time 0.575s\n",
            "I0323 17:06:29.035623 140461325010816 model_lib_v2.py:707] Step 3800 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5617456,\n",
            " 'Loss/localization_loss': 0.56087214,\n",
            " 'Loss/regularization_loss': 0.9750304,\n",
            " 'Loss/total_loss': 2.0976481,\n",
            " 'learning_rate': 0.03520812}\n",
            "I0323 17:06:29.035921 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5617456,\n",
            " 'Loss/localization_loss': 0.56087214,\n",
            " 'Loss/regularization_loss': 0.9750304,\n",
            " 'Loss/total_loss': 2.0976481,\n",
            " 'learning_rate': 0.03520812}\n",
            "INFO:tensorflow:Step 3900 per-step time 0.575s\n",
            "I0323 17:07:26.553653 140461325010816 model_lib_v2.py:707] Step 3900 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.47394922,\n",
            " 'Loss/localization_loss': 0.49515063,\n",
            " 'Loss/regularization_loss': 0.94908434,\n",
            " 'Loss/total_loss': 1.9181843,\n",
            " 'learning_rate': 0.03468645}\n",
            "I0323 17:07:26.553961 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.47394922,\n",
            " 'Loss/localization_loss': 0.49515063,\n",
            " 'Loss/regularization_loss': 0.94908434,\n",
            " 'Loss/total_loss': 1.9181843,\n",
            " 'learning_rate': 0.03468645}\n",
            "INFO:tensorflow:Step 4000 per-step time 0.574s\n",
            "I0323 17:08:23.982761 140461325010816 model_lib_v2.py:707] Step 4000 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.4567043,\n",
            " 'Loss/localization_loss': 0.56873244,\n",
            " 'Loss/regularization_loss': 0.92395806,\n",
            " 'Loss/total_loss': 1.9493948,\n",
            " 'learning_rate': 0.034142137}\n",
            "I0323 17:08:23.983068 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.4567043,\n",
            " 'Loss/localization_loss': 0.56873244,\n",
            " 'Loss/regularization_loss': 0.92395806,\n",
            " 'Loss/total_loss': 1.9493948,\n",
            " 'learning_rate': 0.034142137}\n",
            "INFO:tensorflow:Step 4100 per-step time 0.585s\n",
            "I0323 17:09:22.444860 140461325010816 model_lib_v2.py:707] Step 4100 per-step time 0.585s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.47811392,\n",
            " 'Loss/localization_loss': 0.54820263,\n",
            " 'Loss/regularization_loss': 0.899823,\n",
            " 'Loss/total_loss': 1.9261396,\n",
            " 'learning_rate': 0.03357601}\n",
            "I0323 17:09:22.445184 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.47811392,\n",
            " 'Loss/localization_loss': 0.54820263,\n",
            " 'Loss/regularization_loss': 0.899823,\n",
            " 'Loss/total_loss': 1.9261396,\n",
            " 'learning_rate': 0.03357601}\n",
            "INFO:tensorflow:Step 4200 per-step time 0.575s\n",
            "I0323 17:10:19.918990 140461325010816 model_lib_v2.py:707] Step 4200 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5737177,\n",
            " 'Loss/localization_loss': 0.5712909,\n",
            " 'Loss/regularization_loss': 0.8768041,\n",
            " 'Loss/total_loss': 2.0218127,\n",
            " 'learning_rate': 0.03298896}\n",
            "I0323 17:10:19.919312 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5737177,\n",
            " 'Loss/localization_loss': 0.5712909,\n",
            " 'Loss/regularization_loss': 0.8768041,\n",
            " 'Loss/total_loss': 2.0218127,\n",
            " 'learning_rate': 0.03298896}\n",
            "INFO:tensorflow:Step 4300 per-step time 0.575s\n",
            "I0323 17:11:17.444341 140461325010816 model_lib_v2.py:707] Step 4300 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.69905263,\n",
            " 'Loss/localization_loss': 0.62023723,\n",
            " 'Loss/regularization_loss': 0.85478127,\n",
            " 'Loss/total_loss': 2.1740713,\n",
            " 'learning_rate': 0.032381877}\n",
            "I0323 17:11:17.444668 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.69905263,\n",
            " 'Loss/localization_loss': 0.62023723,\n",
            " 'Loss/regularization_loss': 0.85478127,\n",
            " 'Loss/total_loss': 2.1740713,\n",
            " 'learning_rate': 0.032381877}\n",
            "INFO:tensorflow:Step 4400 per-step time 0.574s\n",
            "I0323 17:12:14.824081 140461325010816 model_lib_v2.py:707] Step 4400 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5647444,\n",
            " 'Loss/localization_loss': 0.41944426,\n",
            " 'Loss/regularization_loss': 0.8336631,\n",
            " 'Loss/total_loss': 1.8178518,\n",
            " 'learning_rate': 0.031755704}\n",
            "I0323 17:12:14.824392 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5647444,\n",
            " 'Loss/localization_loss': 0.41944426,\n",
            " 'Loss/regularization_loss': 0.8336631,\n",
            " 'Loss/total_loss': 1.8178518,\n",
            " 'learning_rate': 0.031755704}\n",
            "INFO:tensorflow:Step 4500 per-step time 0.573s\n",
            "I0323 17:13:12.132798 140461325010816 model_lib_v2.py:707] Step 4500 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.582065,\n",
            " 'Loss/localization_loss': 0.6175323,\n",
            " 'Loss/regularization_loss': 0.8134903,\n",
            " 'Loss/total_loss': 2.0130877,\n",
            " 'learning_rate': 0.031111402}\n",
            "I0323 17:13:12.133097 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.582065,\n",
            " 'Loss/localization_loss': 0.6175323,\n",
            " 'Loss/regularization_loss': 0.8134903,\n",
            " 'Loss/total_loss': 2.0130877,\n",
            " 'learning_rate': 0.031111402}\n",
            "INFO:tensorflow:Step 4600 per-step time 0.574s\n",
            "I0323 17:14:09.491169 140461325010816 model_lib_v2.py:707] Step 4600 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.4111607,\n",
            " 'Loss/localization_loss': 0.48715034,\n",
            " 'Loss/regularization_loss': 0.79426175,\n",
            " 'Loss/total_loss': 1.6925728,\n",
            " 'learning_rate': 0.03044997}\n",
            "I0323 17:14:09.491494 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.4111607,\n",
            " 'Loss/localization_loss': 0.48715034,\n",
            " 'Loss/regularization_loss': 0.79426175,\n",
            " 'Loss/total_loss': 1.6925728,\n",
            " 'learning_rate': 0.03044997}\n",
            "INFO:tensorflow:Step 4700 per-step time 0.574s\n",
            "I0323 17:15:06.845941 140461325010816 model_lib_v2.py:707] Step 4700 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5353744,\n",
            " 'Loss/localization_loss': 0.7281504,\n",
            " 'Loss/regularization_loss': 0.77599156,\n",
            " 'Loss/total_loss': 2.0395164,\n",
            " 'learning_rate': 0.029772423}\n",
            "I0323 17:15:06.846238 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5353744,\n",
            " 'Loss/localization_loss': 0.7281504,\n",
            " 'Loss/regularization_loss': 0.77599156,\n",
            " 'Loss/total_loss': 2.0395164,\n",
            " 'learning_rate': 0.029772423}\n",
            "INFO:tensorflow:Step 4800 per-step time 0.574s\n",
            "I0323 17:16:04.242049 140461325010816 model_lib_v2.py:707] Step 4800 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.52127916,\n",
            " 'Loss/localization_loss': 0.48548472,\n",
            " 'Loss/regularization_loss': 0.7583526,\n",
            " 'Loss/total_loss': 1.7651165,\n",
            " 'learning_rate': 0.029079808}\n",
            "I0323 17:16:04.242354 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.52127916,\n",
            " 'Loss/localization_loss': 0.48548472,\n",
            " 'Loss/regularization_loss': 0.7583526,\n",
            " 'Loss/total_loss': 1.7651165,\n",
            " 'learning_rate': 0.029079808}\n",
            "INFO:tensorflow:Step 4900 per-step time 0.573s\n",
            "I0323 17:17:01.574937 140461325010816 model_lib_v2.py:707] Step 4900 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.73541677,\n",
            " 'Loss/localization_loss': 0.7020717,\n",
            " 'Loss/regularization_loss': 0.74162173,\n",
            " 'Loss/total_loss': 2.1791103,\n",
            " 'learning_rate': 0.028373193}\n",
            "I0323 17:17:01.575243 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.73541677,\n",
            " 'Loss/localization_loss': 0.7020717,\n",
            " 'Loss/regularization_loss': 0.74162173,\n",
            " 'Loss/total_loss': 2.1791103,\n",
            " 'learning_rate': 0.028373193}\n",
            "INFO:tensorflow:Step 5000 per-step time 0.575s\n",
            "I0323 17:17:59.078065 140461325010816 model_lib_v2.py:707] Step 5000 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.60426503,\n",
            " 'Loss/localization_loss': 0.5859297,\n",
            " 'Loss/regularization_loss': 0.725644,\n",
            " 'Loss/total_loss': 1.9158387,\n",
            " 'learning_rate': 0.02765367}\n",
            "I0323 17:17:59.078381 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.60426503,\n",
            " 'Loss/localization_loss': 0.5859297,\n",
            " 'Loss/regularization_loss': 0.725644,\n",
            " 'Loss/total_loss': 1.9158387,\n",
            " 'learning_rate': 0.02765367}\n",
            "INFO:tensorflow:Step 5100 per-step time 0.586s\n",
            "I0323 17:18:57.677983 140461325010816 model_lib_v2.py:707] Step 5100 per-step time 0.586s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.6184025,\n",
            " 'Loss/localization_loss': 0.5170725,\n",
            " 'Loss/regularization_loss': 0.7104053,\n",
            " 'Loss/total_loss': 1.8458803,\n",
            " 'learning_rate': 0.02692234}\n",
            "I0323 17:18:57.678281 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.6184025,\n",
            " 'Loss/localization_loss': 0.5170725,\n",
            " 'Loss/regularization_loss': 0.7104053,\n",
            " 'Loss/total_loss': 1.8458803,\n",
            " 'learning_rate': 0.02692234}\n",
            "INFO:tensorflow:Step 5200 per-step time 0.575s\n",
            "I0323 17:19:55.211092 140461325010816 model_lib_v2.py:707] Step 5200 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.7953904,\n",
            " 'Loss/localization_loss': 0.5927217,\n",
            " 'Loss/regularization_loss': 0.69599974,\n",
            " 'Loss/total_loss': 2.0841117,\n",
            " 'learning_rate': 0.026180338}\n",
            "I0323 17:19:55.211431 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.7953904,\n",
            " 'Loss/localization_loss': 0.5927217,\n",
            " 'Loss/regularization_loss': 0.69599974,\n",
            " 'Loss/total_loss': 2.0841117,\n",
            " 'learning_rate': 0.026180338}\n",
            "INFO:tensorflow:Step 5300 per-step time 0.573s\n",
            "I0323 17:20:52.507242 140461325010816 model_lib_v2.py:707] Step 5300 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.4539492,\n",
            " 'Loss/localization_loss': 0.3457331,\n",
            " 'Loss/regularization_loss': 0.6823735,\n",
            " 'Loss/total_loss': 1.4820559,\n",
            " 'learning_rate': 0.025428807}\n",
            "I0323 17:20:52.507553 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.4539492,\n",
            " 'Loss/localization_loss': 0.3457331,\n",
            " 'Loss/regularization_loss': 0.6823735,\n",
            " 'Loss/total_loss': 1.4820559,\n",
            " 'learning_rate': 0.025428807}\n",
            "INFO:tensorflow:Step 5400 per-step time 0.573s\n",
            "I0323 17:21:49.844342 140461325010816 model_lib_v2.py:707] Step 5400 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5265749,\n",
            " 'Loss/localization_loss': 0.49337763,\n",
            " 'Loss/regularization_loss': 0.6693703,\n",
            " 'Loss/total_loss': 1.6893228,\n",
            " 'learning_rate': 0.024668908}\n",
            "I0323 17:21:49.844664 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5265749,\n",
            " 'Loss/localization_loss': 0.49337763,\n",
            " 'Loss/regularization_loss': 0.6693703,\n",
            " 'Loss/total_loss': 1.6893228,\n",
            " 'learning_rate': 0.024668908}\n",
            "INFO:tensorflow:Step 5500 per-step time 0.575s\n",
            "I0323 17:22:47.325942 140461325010816 model_lib_v2.py:707] Step 5500 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5828086,\n",
            " 'Loss/localization_loss': 0.6884712,\n",
            " 'Loss/regularization_loss': 0.657001,\n",
            " 'Loss/total_loss': 1.9282808,\n",
            " 'learning_rate': 0.023901805}\n",
            "I0323 17:22:47.326253 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5828086,\n",
            " 'Loss/localization_loss': 0.6884712,\n",
            " 'Loss/regularization_loss': 0.657001,\n",
            " 'Loss/total_loss': 1.9282808,\n",
            " 'learning_rate': 0.023901805}\n",
            "INFO:tensorflow:Step 5600 per-step time 0.574s\n",
            "I0323 17:23:44.692378 140461325010816 model_lib_v2.py:707] Step 5600 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.41699237,\n",
            " 'Loss/localization_loss': 0.35764328,\n",
            " 'Loss/regularization_loss': 0.6452158,\n",
            " 'Loss/total_loss': 1.4198515,\n",
            " 'learning_rate': 0.02312869}\n",
            "I0323 17:23:44.692700 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.41699237,\n",
            " 'Loss/localization_loss': 0.35764328,\n",
            " 'Loss/regularization_loss': 0.6452158,\n",
            " 'Loss/total_loss': 1.4198515,\n",
            " 'learning_rate': 0.02312869}\n",
            "INFO:tensorflow:Step 5700 per-step time 0.574s\n",
            "I0323 17:24:42.067078 140461325010816 model_lib_v2.py:707] Step 5700 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.55478054,\n",
            " 'Loss/localization_loss': 0.5968363,\n",
            " 'Loss/regularization_loss': 0.63401574,\n",
            " 'Loss/total_loss': 1.7856326,\n",
            " 'learning_rate': 0.022350745}\n",
            "I0323 17:24:42.067389 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.55478054,\n",
            " 'Loss/localization_loss': 0.5968363,\n",
            " 'Loss/regularization_loss': 0.63401574,\n",
            " 'Loss/total_loss': 1.7856326,\n",
            " 'learning_rate': 0.022350745}\n",
            "INFO:tensorflow:Step 5800 per-step time 0.572s\n",
            "I0323 17:25:39.303450 140461325010816 model_lib_v2.py:707] Step 5800 per-step time 0.572s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.74817204,\n",
            " 'Loss/localization_loss': 0.51165456,\n",
            " 'Loss/regularization_loss': 0.6234063,\n",
            " 'Loss/total_loss': 1.883233,\n",
            " 'learning_rate': 0.02156918}\n",
            "I0323 17:25:39.303772 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.74817204,\n",
            " 'Loss/localization_loss': 0.51165456,\n",
            " 'Loss/regularization_loss': 0.6234063,\n",
            " 'Loss/total_loss': 1.883233,\n",
            " 'learning_rate': 0.02156918}\n",
            "INFO:tensorflow:Step 5900 per-step time 0.573s\n",
            "I0323 17:26:36.649979 140461325010816 model_lib_v2.py:707] Step 5900 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5917206,\n",
            " 'Loss/localization_loss': 0.4951747,\n",
            " 'Loss/regularization_loss': 0.61342114,\n",
            " 'Loss/total_loss': 1.7003164,\n",
            " 'learning_rate': 0.020785196}\n",
            "I0323 17:26:36.650283 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5917206,\n",
            " 'Loss/localization_loss': 0.4951747,\n",
            " 'Loss/regularization_loss': 0.61342114,\n",
            " 'Loss/total_loss': 1.7003164,\n",
            " 'learning_rate': 0.020785196}\n",
            "INFO:tensorflow:Step 6000 per-step time 0.574s\n",
            "I0323 17:27:34.019685 140461325010816 model_lib_v2.py:707] Step 6000 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.6476632,\n",
            " 'Loss/localization_loss': 0.59618586,\n",
            " 'Loss/regularization_loss': 0.6038578,\n",
            " 'Loss/total_loss': 1.8477068,\n",
            " 'learning_rate': 0.019999998}\n",
            "I0323 17:27:34.020020 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.6476632,\n",
            " 'Loss/localization_loss': 0.59618586,\n",
            " 'Loss/regularization_loss': 0.6038578,\n",
            " 'Loss/total_loss': 1.8477068,\n",
            " 'learning_rate': 0.019999998}\n",
            "INFO:tensorflow:Step 6100 per-step time 0.583s\n",
            "I0323 17:28:32.345170 140461325010816 model_lib_v2.py:707] Step 6100 per-step time 0.583s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.48783648,\n",
            " 'Loss/localization_loss': 0.6547682,\n",
            " 'Loss/regularization_loss': 0.594816,\n",
            " 'Loss/total_loss': 1.7374208,\n",
            " 'learning_rate': 0.019214803}\n",
            "I0323 17:28:32.345530 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.48783648,\n",
            " 'Loss/localization_loss': 0.6547682,\n",
            " 'Loss/regularization_loss': 0.594816,\n",
            " 'Loss/total_loss': 1.7374208,\n",
            " 'learning_rate': 0.019214803}\n",
            "INFO:tensorflow:Step 6200 per-step time 0.573s\n",
            "I0323 17:29:29.680657 140461325010816 model_lib_v2.py:707] Step 6200 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.61752963,\n",
            " 'Loss/localization_loss': 0.5570809,\n",
            " 'Loss/regularization_loss': 0.5863242,\n",
            " 'Loss/total_loss': 1.7609348,\n",
            " 'learning_rate': 0.018430816}\n",
            "I0323 17:29:29.681012 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.61752963,\n",
            " 'Loss/localization_loss': 0.5570809,\n",
            " 'Loss/regularization_loss': 0.5863242,\n",
            " 'Loss/total_loss': 1.7609348,\n",
            " 'learning_rate': 0.018430816}\n",
            "INFO:tensorflow:Step 6300 per-step time 0.574s\n",
            "I0323 17:30:27.072705 140461325010816 model_lib_v2.py:707] Step 6300 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.46750572,\n",
            " 'Loss/localization_loss': 0.48336223,\n",
            " 'Loss/regularization_loss': 0.5782949,\n",
            " 'Loss/total_loss': 1.5291629,\n",
            " 'learning_rate': 0.017649252}\n",
            "I0323 17:30:27.073040 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.46750572,\n",
            " 'Loss/localization_loss': 0.48336223,\n",
            " 'Loss/regularization_loss': 0.5782949,\n",
            " 'Loss/total_loss': 1.5291629,\n",
            " 'learning_rate': 0.017649252}\n",
            "INFO:tensorflow:Step 6400 per-step time 0.574s\n",
            "I0323 17:31:24.460612 140461325010816 model_lib_v2.py:707] Step 6400 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.55434996,\n",
            " 'Loss/localization_loss': 0.5613076,\n",
            " 'Loss/regularization_loss': 0.5706297,\n",
            " 'Loss/total_loss': 1.6862873,\n",
            " 'learning_rate': 0.01687131}\n",
            "I0323 17:31:24.460919 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.55434996,\n",
            " 'Loss/localization_loss': 0.5613076,\n",
            " 'Loss/regularization_loss': 0.5706297,\n",
            " 'Loss/total_loss': 1.6862873,\n",
            " 'learning_rate': 0.01687131}\n",
            "INFO:tensorflow:Step 6500 per-step time 0.574s\n",
            "I0323 17:32:21.822916 140461325010816 model_lib_v2.py:707] Step 6500 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5790348,\n",
            " 'Loss/localization_loss': 0.5364688,\n",
            " 'Loss/regularization_loss': 0.56348616,\n",
            " 'Loss/total_loss': 1.6789896,\n",
            " 'learning_rate': 0.016098194}\n",
            "I0323 17:32:21.823226 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5790348,\n",
            " 'Loss/localization_loss': 0.5364688,\n",
            " 'Loss/regularization_loss': 0.56348616,\n",
            " 'Loss/total_loss': 1.6789896,\n",
            " 'learning_rate': 0.016098194}\n",
            "INFO:tensorflow:Step 6600 per-step time 0.573s\n",
            "I0323 17:33:19.152739 140461325010816 model_lib_v2.py:707] Step 6600 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5772118,\n",
            " 'Loss/localization_loss': 0.5815632,\n",
            " 'Loss/regularization_loss': 0.55672413,\n",
            " 'Loss/total_loss': 1.7154992,\n",
            " 'learning_rate': 0.015331091}\n",
            "I0323 17:33:19.153039 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5772118,\n",
            " 'Loss/localization_loss': 0.5815632,\n",
            " 'Loss/regularization_loss': 0.55672413,\n",
            " 'Loss/total_loss': 1.7154992,\n",
            " 'learning_rate': 0.015331091}\n",
            "INFO:tensorflow:Step 6700 per-step time 0.573s\n",
            "I0323 17:34:16.484757 140461325010816 model_lib_v2.py:707] Step 6700 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.51413906,\n",
            " 'Loss/localization_loss': 0.58204067,\n",
            " 'Loss/regularization_loss': 0.55041236,\n",
            " 'Loss/total_loss': 1.6465921,\n",
            " 'learning_rate': 0.014571187}\n",
            "I0323 17:34:16.485060 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.51413906,\n",
            " 'Loss/localization_loss': 0.58204067,\n",
            " 'Loss/regularization_loss': 0.55041236,\n",
            " 'Loss/total_loss': 1.6465921,\n",
            " 'learning_rate': 0.014571187}\n",
            "INFO:tensorflow:Step 6800 per-step time 0.574s\n",
            "I0323 17:35:13.846749 140461325010816 model_lib_v2.py:707] Step 6800 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.43786153,\n",
            " 'Loss/localization_loss': 0.4021089,\n",
            " 'Loss/regularization_loss': 0.5444432,\n",
            " 'Loss/total_loss': 1.3844137,\n",
            " 'learning_rate': 0.013819658}\n",
            "I0323 17:35:13.847064 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.43786153,\n",
            " 'Loss/localization_loss': 0.4021089,\n",
            " 'Loss/regularization_loss': 0.5444432,\n",
            " 'Loss/total_loss': 1.3844137,\n",
            " 'learning_rate': 0.013819658}\n",
            "INFO:tensorflow:Step 6900 per-step time 0.573s\n",
            "I0323 17:36:11.163233 140461325010816 model_lib_v2.py:707] Step 6900 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5866544,\n",
            " 'Loss/localization_loss': 0.600907,\n",
            " 'Loss/regularization_loss': 0.5388681,\n",
            " 'Loss/total_loss': 1.7264297,\n",
            " 'learning_rate': 0.013077657}\n",
            "I0323 17:36:11.163571 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5866544,\n",
            " 'Loss/localization_loss': 0.600907,\n",
            " 'Loss/regularization_loss': 0.5388681,\n",
            " 'Loss/total_loss': 1.7264297,\n",
            " 'learning_rate': 0.013077657}\n",
            "INFO:tensorflow:Step 7000 per-step time 0.574s\n",
            "I0323 17:37:08.598173 140461325010816 model_lib_v2.py:707] Step 7000 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.34093642,\n",
            " 'Loss/localization_loss': 0.2900128,\n",
            " 'Loss/regularization_loss': 0.53366536,\n",
            " 'Loss/total_loss': 1.1646147,\n",
            " 'learning_rate': 0.012346329}\n",
            "I0323 17:37:08.598488 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.34093642,\n",
            " 'Loss/localization_loss': 0.2900128,\n",
            " 'Loss/regularization_loss': 0.53366536,\n",
            " 'Loss/total_loss': 1.1646147,\n",
            " 'learning_rate': 0.012346329}\n",
            "INFO:tensorflow:Step 7100 per-step time 0.586s\n",
            "I0323 17:38:07.240613 140461325010816 model_lib_v2.py:707] Step 7100 per-step time 0.586s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.60425085,\n",
            " 'Loss/localization_loss': 0.55845374,\n",
            " 'Loss/regularization_loss': 0.5287654,\n",
            " 'Loss/total_loss': 1.6914699,\n",
            " 'learning_rate': 0.011626803}\n",
            "I0323 17:38:07.240934 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.60425085,\n",
            " 'Loss/localization_loss': 0.55845374,\n",
            " 'Loss/regularization_loss': 0.5287654,\n",
            " 'Loss/total_loss': 1.6914699,\n",
            " 'learning_rate': 0.011626803}\n",
            "INFO:tensorflow:Step 7200 per-step time 0.574s\n",
            "I0323 17:39:04.651638 140461325010816 model_lib_v2.py:707] Step 7200 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5080936,\n",
            " 'Loss/localization_loss': 0.39637014,\n",
            " 'Loss/regularization_loss': 0.52421325,\n",
            " 'Loss/total_loss': 1.4286771,\n",
            " 'learning_rate': 0.010920188}\n",
            "I0323 17:39:04.651934 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5080936,\n",
            " 'Loss/localization_loss': 0.39637014,\n",
            " 'Loss/regularization_loss': 0.52421325,\n",
            " 'Loss/total_loss': 1.4286771,\n",
            " 'learning_rate': 0.010920188}\n",
            "INFO:tensorflow:Step 7300 per-step time 0.573s\n",
            "I0323 17:40:01.930641 140461325010816 model_lib_v2.py:707] Step 7300 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.67377293,\n",
            " 'Loss/localization_loss': 0.5651088,\n",
            " 'Loss/regularization_loss': 0.51995236,\n",
            " 'Loss/total_loss': 1.7588341,\n",
            " 'learning_rate': 0.010227573}\n",
            "I0323 17:40:01.930953 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.67377293,\n",
            " 'Loss/localization_loss': 0.5651088,\n",
            " 'Loss/regularization_loss': 0.51995236,\n",
            " 'Loss/total_loss': 1.7588341,\n",
            " 'learning_rate': 0.010227573}\n",
            "INFO:tensorflow:Step 7400 per-step time 0.574s\n",
            "I0323 17:40:59.352809 140461325010816 model_lib_v2.py:707] Step 7400 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.29586264,\n",
            " 'Loss/localization_loss': 0.3227667,\n",
            " 'Loss/regularization_loss': 0.51602656,\n",
            " 'Loss/total_loss': 1.134656,\n",
            " 'learning_rate': 0.009550026}\n",
            "I0323 17:40:59.353123 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.29586264,\n",
            " 'Loss/localization_loss': 0.3227667,\n",
            " 'Loss/regularization_loss': 0.51602656,\n",
            " 'Loss/total_loss': 1.134656,\n",
            " 'learning_rate': 0.009550026}\n",
            "INFO:tensorflow:Step 7500 per-step time 0.574s\n",
            "I0323 17:41:56.745086 140461325010816 model_lib_v2.py:707] Step 7500 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.41680598,\n",
            " 'Loss/localization_loss': 0.5909187,\n",
            " 'Loss/regularization_loss': 0.5124363,\n",
            " 'Loss/total_loss': 1.520161,\n",
            " 'learning_rate': 0.008888596}\n",
            "I0323 17:41:56.745393 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.41680598,\n",
            " 'Loss/localization_loss': 0.5909187,\n",
            " 'Loss/regularization_loss': 0.5124363,\n",
            " 'Loss/total_loss': 1.520161,\n",
            " 'learning_rate': 0.008888596}\n",
            "INFO:tensorflow:Step 7600 per-step time 0.573s\n",
            "I0323 17:42:54.058220 140461325010816 model_lib_v2.py:707] Step 7600 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5079947,\n",
            " 'Loss/localization_loss': 0.47584552,\n",
            " 'Loss/regularization_loss': 0.50908786,\n",
            " 'Loss/total_loss': 1.492928,\n",
            " 'learning_rate': 0.008244291}\n",
            "I0323 17:42:54.058532 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5079947,\n",
            " 'Loss/localization_loss': 0.47584552,\n",
            " 'Loss/regularization_loss': 0.50908786,\n",
            " 'Loss/total_loss': 1.492928,\n",
            " 'learning_rate': 0.008244291}\n",
            "INFO:tensorflow:Step 7700 per-step time 0.573s\n",
            "I0323 17:43:51.319200 140461325010816 model_lib_v2.py:707] Step 7700 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5510475,\n",
            " 'Loss/localization_loss': 0.2971513,\n",
            " 'Loss/regularization_loss': 0.5059833,\n",
            " 'Loss/total_loss': 1.354182,\n",
            " 'learning_rate': 0.007618121}\n",
            "I0323 17:43:51.319599 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5510475,\n",
            " 'Loss/localization_loss': 0.2971513,\n",
            " 'Loss/regularization_loss': 0.5059833,\n",
            " 'Loss/total_loss': 1.354182,\n",
            " 'learning_rate': 0.007618121}\n",
            "INFO:tensorflow:Step 7800 per-step time 0.574s\n",
            "I0323 17:44:48.712496 140461325010816 model_lib_v2.py:707] Step 7800 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.60424775,\n",
            " 'Loss/localization_loss': 0.5289576,\n",
            " 'Loss/regularization_loss': 0.5031233,\n",
            " 'Loss/total_loss': 1.6363287,\n",
            " 'learning_rate': 0.0070110355}\n",
            "I0323 17:44:48.712796 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.60424775,\n",
            " 'Loss/localization_loss': 0.5289576,\n",
            " 'Loss/regularization_loss': 0.5031233,\n",
            " 'Loss/total_loss': 1.6363287,\n",
            " 'learning_rate': 0.0070110355}\n",
            "INFO:tensorflow:Step 7900 per-step time 0.574s\n",
            "I0323 17:45:46.067183 140461325010816 model_lib_v2.py:707] Step 7900 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.3690875,\n",
            " 'Loss/localization_loss': 0.39334333,\n",
            " 'Loss/regularization_loss': 0.5005138,\n",
            " 'Loss/total_loss': 1.2629446,\n",
            " 'learning_rate': 0.0064239847}\n",
            "I0323 17:45:46.067517 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.3690875,\n",
            " 'Loss/localization_loss': 0.39334333,\n",
            " 'Loss/regularization_loss': 0.5005138,\n",
            " 'Loss/total_loss': 1.2629446,\n",
            " 'learning_rate': 0.0064239847}\n",
            "INFO:tensorflow:Step 8000 per-step time 0.573s\n",
            "I0323 17:46:43.412373 140461325010816 model_lib_v2.py:707] Step 8000 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.42161736,\n",
            " 'Loss/localization_loss': 0.46626806,\n",
            " 'Loss/regularization_loss': 0.49814093,\n",
            " 'Loss/total_loss': 1.3860264,\n",
            " 'learning_rate': 0.0058578644}\n",
            "I0323 17:46:43.412680 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.42161736,\n",
            " 'Loss/localization_loss': 0.46626806,\n",
            " 'Loss/regularization_loss': 0.49814093,\n",
            " 'Loss/total_loss': 1.3860264,\n",
            " 'learning_rate': 0.0058578644}\n",
            "INFO:tensorflow:Step 8100 per-step time 0.584s\n",
            "I0323 17:47:41.806936 140461325010816 model_lib_v2.py:707] Step 8100 per-step time 0.584s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.41836452,\n",
            " 'Loss/localization_loss': 0.28595954,\n",
            " 'Loss/regularization_loss': 0.4959827,\n",
            " 'Loss/total_loss': 1.2003068,\n",
            " 'learning_rate': 0.0053135487}\n",
            "I0323 17:47:41.807247 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.41836452,\n",
            " 'Loss/localization_loss': 0.28595954,\n",
            " 'Loss/regularization_loss': 0.4959827,\n",
            " 'Loss/total_loss': 1.2003068,\n",
            " 'learning_rate': 0.0053135487}\n",
            "INFO:tensorflow:Step 8200 per-step time 0.575s\n",
            "I0323 17:48:39.345178 140461325010816 model_lib_v2.py:707] Step 8200 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5929413,\n",
            " 'Loss/localization_loss': 0.5973289,\n",
            " 'Loss/regularization_loss': 0.49404043,\n",
            " 'Loss/total_loss': 1.6843107,\n",
            " 'learning_rate': 0.0047918796}\n",
            "I0323 17:48:39.345615 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5929413,\n",
            " 'Loss/localization_loss': 0.5973289,\n",
            " 'Loss/regularization_loss': 0.49404043,\n",
            " 'Loss/total_loss': 1.6843107,\n",
            " 'learning_rate': 0.0047918796}\n",
            "INFO:tensorflow:Step 8300 per-step time 0.574s\n",
            "I0323 17:49:36.718522 140461325010816 model_lib_v2.py:707] Step 8300 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.45898926,\n",
            " 'Loss/localization_loss': 0.51462233,\n",
            " 'Loss/regularization_loss': 0.49228895,\n",
            " 'Loss/total_loss': 1.4659005,\n",
            " 'learning_rate': 0.0042936574}\n",
            "I0323 17:49:36.718833 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.45898926,\n",
            " 'Loss/localization_loss': 0.51462233,\n",
            " 'Loss/regularization_loss': 0.49228895,\n",
            " 'Loss/total_loss': 1.4659005,\n",
            " 'learning_rate': 0.0042936574}\n",
            "INFO:tensorflow:Step 8400 per-step time 0.574s\n",
            "I0323 17:50:34.128850 140461325010816 model_lib_v2.py:707] Step 8400 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.6061051,\n",
            " 'Loss/localization_loss': 0.55994964,\n",
            " 'Loss/regularization_loss': 0.49073148,\n",
            " 'Loss/total_loss': 1.6567862,\n",
            " 'learning_rate': 0.0038196587}\n",
            "I0323 17:50:34.129147 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.6061051,\n",
            " 'Loss/localization_loss': 0.55994964,\n",
            " 'Loss/regularization_loss': 0.49073148,\n",
            " 'Loss/total_loss': 1.6567862,\n",
            " 'learning_rate': 0.0038196587}\n",
            "INFO:tensorflow:Step 8500 per-step time 0.575s\n",
            "I0323 17:51:31.676625 140461325010816 model_lib_v2.py:707] Step 8500 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5118948,\n",
            " 'Loss/localization_loss': 0.56100535,\n",
            " 'Loss/regularization_loss': 0.4893483,\n",
            " 'Loss/total_loss': 1.5622485,\n",
            " 'learning_rate': 0.0033706068}\n",
            "I0323 17:51:31.676945 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5118948,\n",
            " 'Loss/localization_loss': 0.56100535,\n",
            " 'Loss/regularization_loss': 0.4893483,\n",
            " 'Loss/total_loss': 1.5622485,\n",
            " 'learning_rate': 0.0033706068}\n",
            "INFO:tensorflow:Step 8600 per-step time 0.574s\n",
            "I0323 17:52:29.111541 140461325010816 model_lib_v2.py:707] Step 8600 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.6049685,\n",
            " 'Loss/localization_loss': 0.41128418,\n",
            " 'Loss/regularization_loss': 0.4881355,\n",
            " 'Loss/total_loss': 1.5043881,\n",
            " 'learning_rate': 0.0029471957}\n",
            "I0323 17:52:29.111861 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.6049685,\n",
            " 'Loss/localization_loss': 0.41128418,\n",
            " 'Loss/regularization_loss': 0.4881355,\n",
            " 'Loss/total_loss': 1.5043881,\n",
            " 'learning_rate': 0.0029471957}\n",
            "INFO:tensorflow:Step 8700 per-step time 0.574s\n",
            "I0323 17:53:26.467637 140461325010816 model_lib_v2.py:707] Step 8700 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.4130017,\n",
            " 'Loss/localization_loss': 0.35794747,\n",
            " 'Loss/regularization_loss': 0.48707953,\n",
            " 'Loss/total_loss': 1.2580286,\n",
            " 'learning_rate': 0.0025500786}\n",
            "I0323 17:53:26.467955 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.4130017,\n",
            " 'Loss/localization_loss': 0.35794747,\n",
            " 'Loss/regularization_loss': 0.48707953,\n",
            " 'Loss/total_loss': 1.2580286,\n",
            " 'learning_rate': 0.0025500786}\n",
            "INFO:tensorflow:Step 8800 per-step time 0.574s\n",
            "I0323 17:54:23.880778 140461325010816 model_lib_v2.py:707] Step 8800 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.51982164,\n",
            " 'Loss/localization_loss': 0.5270968,\n",
            " 'Loss/regularization_loss': 0.48617035,\n",
            " 'Loss/total_loss': 1.5330887,\n",
            " 'learning_rate': 0.0021798706}\n",
            "I0323 17:54:23.881085 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.51982164,\n",
            " 'Loss/localization_loss': 0.5270968,\n",
            " 'Loss/regularization_loss': 0.48617035,\n",
            " 'Loss/total_loss': 1.5330887,\n",
            " 'learning_rate': 0.0021798706}\n",
            "INFO:tensorflow:Step 8900 per-step time 0.573s\n",
            "I0323 17:55:21.213285 140461325010816 model_lib_v2.py:707] Step 8900 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.5730077,\n",
            " 'Loss/localization_loss': 0.50704074,\n",
            " 'Loss/regularization_loss': 0.48539308,\n",
            " 'Loss/total_loss': 1.5654415,\n",
            " 'learning_rate': 0.0018371355}\n",
            "I0323 17:55:21.213602 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.5730077,\n",
            " 'Loss/localization_loss': 0.50704074,\n",
            " 'Loss/regularization_loss': 0.48539308,\n",
            " 'Loss/total_loss': 1.5654415,\n",
            " 'learning_rate': 0.0018371355}\n",
            "INFO:tensorflow:Step 9000 per-step time 0.575s\n",
            "I0323 17:56:18.672146 140461325010816 model_lib_v2.py:707] Step 9000 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.41533032,\n",
            " 'Loss/localization_loss': 0.43164888,\n",
            " 'Loss/regularization_loss': 0.48474288,\n",
            " 'Loss/total_loss': 1.331722,\n",
            " 'learning_rate': 0.0015224098}\n",
            "I0323 17:56:18.672459 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.41533032,\n",
            " 'Loss/localization_loss': 0.43164888,\n",
            " 'Loss/regularization_loss': 0.48474288,\n",
            " 'Loss/total_loss': 1.331722,\n",
            " 'learning_rate': 0.0015224098}\n",
            "INFO:tensorflow:Step 9100 per-step time 0.586s\n",
            "I0323 17:57:17.254706 140461325010816 model_lib_v2.py:707] Step 9100 per-step time 0.586s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.43100995,\n",
            " 'Loss/localization_loss': 0.3922662,\n",
            " 'Loss/regularization_loss': 0.48419824,\n",
            " 'Loss/total_loss': 1.3074744,\n",
            " 'learning_rate': 0.0012361717}\n",
            "I0323 17:57:17.255017 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.43100995,\n",
            " 'Loss/localization_loss': 0.3922662,\n",
            " 'Loss/regularization_loss': 0.48419824,\n",
            " 'Loss/total_loss': 1.3074744,\n",
            " 'learning_rate': 0.0012361717}\n",
            "INFO:tensorflow:Step 9200 per-step time 0.574s\n",
            "I0323 17:58:14.617825 140461325010816 model_lib_v2.py:707] Step 9200 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.38430882,\n",
            " 'Loss/localization_loss': 0.40050045,\n",
            " 'Loss/regularization_loss': 0.48377103,\n",
            " 'Loss/total_loss': 1.2685802,\n",
            " 'learning_rate': 0.0009788703}\n",
            "I0323 17:58:14.618145 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.38430882,\n",
            " 'Loss/localization_loss': 0.40050045,\n",
            " 'Loss/regularization_loss': 0.48377103,\n",
            " 'Loss/total_loss': 1.2685802,\n",
            " 'learning_rate': 0.0009788703}\n",
            "INFO:tensorflow:Step 9300 per-step time 0.574s\n",
            "I0323 17:59:12.009543 140461325010816 model_lib_v2.py:707] Step 9300 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.43682617,\n",
            " 'Loss/localization_loss': 0.39687237,\n",
            " 'Loss/regularization_loss': 0.48343727,\n",
            " 'Loss/total_loss': 1.3171358,\n",
            " 'learning_rate': 0.0007508957}\n",
            "I0323 17:59:12.009862 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.43682617,\n",
            " 'Loss/localization_loss': 0.39687237,\n",
            " 'Loss/regularization_loss': 0.48343727,\n",
            " 'Loss/total_loss': 1.3171358,\n",
            " 'learning_rate': 0.0007508957}\n",
            "INFO:tensorflow:Step 9400 per-step time 0.574s\n",
            "I0323 18:00:09.404526 140461325010816 model_lib_v2.py:707] Step 9400 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.44087946,\n",
            " 'Loss/localization_loss': 0.46013862,\n",
            " 'Loss/regularization_loss': 0.48318502,\n",
            " 'Loss/total_loss': 1.3842031,\n",
            " 'learning_rate': 0.0005526006}\n",
            "I0323 18:00:09.404867 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.44087946,\n",
            " 'Loss/localization_loss': 0.46013862,\n",
            " 'Loss/regularization_loss': 0.48318502,\n",
            " 'Loss/total_loss': 1.3842031,\n",
            " 'learning_rate': 0.0005526006}\n",
            "INFO:tensorflow:Step 9500 per-step time 0.575s\n",
            "I0323 18:01:06.873753 140461325010816 model_lib_v2.py:707] Step 9500 per-step time 0.575s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.4417837,\n",
            " 'Loss/localization_loss': 0.502584,\n",
            " 'Loss/regularization_loss': 0.48300004,\n",
            " 'Loss/total_loss': 1.4273677,\n",
            " 'learning_rate': 0.0003842938}\n",
            "I0323 18:01:06.874061 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.4417837,\n",
            " 'Loss/localization_loss': 0.502584,\n",
            " 'Loss/regularization_loss': 0.48300004,\n",
            " 'Loss/total_loss': 1.4273677,\n",
            " 'learning_rate': 0.0003842938}\n",
            "INFO:tensorflow:Step 9600 per-step time 0.573s\n",
            "I0323 18:02:04.189365 140461325010816 model_lib_v2.py:707] Step 9600 per-step time 0.573s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.58581924,\n",
            " 'Loss/localization_loss': 0.47718108,\n",
            " 'Loss/regularization_loss': 0.48287523,\n",
            " 'Loss/total_loss': 1.5458755,\n",
            " 'learning_rate': 0.00024623275}\n",
            "I0323 18:02:04.189683 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.58581924,\n",
            " 'Loss/localization_loss': 0.47718108,\n",
            " 'Loss/regularization_loss': 0.48287523,\n",
            " 'Loss/total_loss': 1.5458755,\n",
            " 'learning_rate': 0.00024623275}\n",
            "INFO:tensorflow:Step 9700 per-step time 0.574s\n",
            "I0323 18:03:01.599175 140461325010816 model_lib_v2.py:707] Step 9700 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.53610396,\n",
            " 'Loss/localization_loss': 0.47140574,\n",
            " 'Loss/regularization_loss': 0.48279834,\n",
            " 'Loss/total_loss': 1.490308,\n",
            " 'learning_rate': 0.00013863086}\n",
            "I0323 18:03:01.599542 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.53610396,\n",
            " 'Loss/localization_loss': 0.47140574,\n",
            " 'Loss/regularization_loss': 0.48279834,\n",
            " 'Loss/total_loss': 1.490308,\n",
            " 'learning_rate': 0.00013863086}\n",
            "INFO:tensorflow:Step 9800 per-step time 0.574s\n",
            "I0323 18:03:59.007383 140461325010816 model_lib_v2.py:707] Step 9800 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.2907614,\n",
            " 'Loss/localization_loss': 0.34282073,\n",
            " 'Loss/regularization_loss': 0.4827578,\n",
            " 'Loss/total_loss': 1.1163399,\n",
            " 'learning_rate': 6.165266e-05}\n",
            "I0323 18:03:59.007713 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.2907614,\n",
            " 'Loss/localization_loss': 0.34282073,\n",
            " 'Loss/regularization_loss': 0.4827578,\n",
            " 'Loss/total_loss': 1.1163399,\n",
            " 'learning_rate': 6.165266e-05}\n",
            "INFO:tensorflow:Step 9900 per-step time 0.574s\n",
            "I0323 18:04:56.451549 140461325010816 model_lib_v2.py:707] Step 9900 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.43884218,\n",
            " 'Loss/localization_loss': 0.48422113,\n",
            " 'Loss/regularization_loss': 0.48274246,\n",
            " 'Loss/total_loss': 1.4058057,\n",
            " 'learning_rate': 1.541972e-05}\n",
            "I0323 18:04:56.451849 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.43884218,\n",
            " 'Loss/localization_loss': 0.48422113,\n",
            " 'Loss/regularization_loss': 0.48274246,\n",
            " 'Loss/total_loss': 1.4058057,\n",
            " 'learning_rate': 1.541972e-05}\n",
            "INFO:tensorflow:Step 10000 per-step time 0.574s\n",
            "I0323 18:05:53.866289 140461325010816 model_lib_v2.py:707] Step 10000 per-step time 0.574s\n",
            "INFO:tensorflow:{'Loss/classification_loss': 0.38589567,\n",
            " 'Loss/localization_loss': 0.42315003,\n",
            " 'Loss/regularization_loss': 0.4827402,\n",
            " 'Loss/total_loss': 1.2917858,\n",
            " 'learning_rate': 0.0}\n",
            "I0323 18:05:53.866616 140461325010816 model_lib_v2.py:708] {'Loss/classification_loss': 0.38589567,\n",
            " 'Loss/localization_loss': 0.42315003,\n",
            " 'Loss/regularization_loss': 0.4827402,\n",
            " 'Loss/total_loss': 1.2917858,\n",
            " 'learning_rate': 0.0}\n"
          ]
        }
      ],
      "source": [
        "!python model_main_tf2.py --model_dir=/content/tensorflow2/workspace/training_demo/models/my_ssd_resnet50_v1_fpn --pipeline_config_path=/content/tensorflow2/workspace/training_demo/models/my_ssd_resnet50_v1_fpn/pipeline.config"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# !pip uninstall -y tensorboard tb-nightly &&\n",
        "# !pip install tb-nightly  # must have at least tb-nightly==2.5.0a20210316"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 696
        },
        "id": "xGclBqPFR_YK",
        "outputId": "832ee59a-6b98-478b-a039-0f32adfdedd7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/bin/bash: -c: line 1: syntax error: unexpected end of file\n",
            "Collecting tb-nightly\n",
            "  Downloading tb_nightly-2.9.0a20220318-py3-none-any.whl (5.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.8 MB 5.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (1.0.1)\n",
            "Requirement already satisfied: numpy>=1.12.0 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (1.21.5)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (2.27.1)\n",
            "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (1.0.0)\n",
            "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (0.6.1)\n",
            "Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (0.37.1)\n",
            "Requirement already satisfied: protobuf>=3.9.2 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (3.19.4)\n",
            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (1.35.0)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (0.4.6)\n",
            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (57.4.0)\n",
            "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (1.8.1)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (3.3.6)\n",
            "Requirement already satisfied: grpcio>=1.24.3 in /usr/local/lib/python3.7/dist-packages (from tb-nightly) (1.44.0)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from absl-py>=0.4->tb-nightly) (1.15.0)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tb-nightly) (0.2.8)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tb-nightly) (4.8)\n",
            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tb-nightly) (4.2.4)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tb-nightly) (1.3.1)\n",
            "Requirement already satisfied: importlib-metadata>=4.4 in /usr/local/lib/python3.7/dist-packages (from markdown>=2.6.8->tb-nightly) (4.11.2)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tb-nightly) (3.10.0.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tb-nightly) (3.7.0)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.7/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tb-nightly) (0.4.8)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tb-nightly) (1.24.3)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tb-nightly) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tb-nightly) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tb-nightly) (2021.10.8)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tb-nightly) (3.2.0)\n",
            "Installing collected packages: tb-nightly\n",
            "Successfully installed tb-nightly-2.9.0a20220318\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "tensorboard"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# !pip uninstall tb-nightly tensorboardX tensorboard\n",
        "# !pip install tensorboard"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 938
        },
        "id": "XGNUVkyLSc7a",
        "outputId": "6456ca0f-3ddf-4926-93b0-83fcd70f348e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found existing installation: tb-nightly 2.9.0a20220317\n",
            "Uninstalling tb-nightly-2.9.0a20220317:\n",
            "  Would remove:\n",
            "    /usr/local/bin/tensorboard\n",
            "    /usr/local/lib/python3.7/dist-packages/tb_nightly-2.9.0a20220317.dist-info/*\n",
            "    /usr/local/lib/python3.7/dist-packages/tensorboard/*\n",
            "Proceed (y/n)? Y\n",
            "  Successfully uninstalled tb-nightly-2.9.0a20220317\n",
            "\u001b[33mWARNING: Skipping tensorboardX as it is not installed.\u001b[0m\n",
            "Found existing installation: tensorboard 2.8.0\n",
            "Uninstalling tensorboard-2.8.0:\n",
            "  Would remove:\n",
            "    /usr/local/lib/python3.7/dist-packages/tensorboard-2.8.0.dist-info/*\n",
            "Proceed (y/n)? Y\n",
            "  Successfully uninstalled tensorboard-2.8.0\n",
            "Collecting tensorboard\n",
            "  Downloading tensorboard-2.8.0-py3-none-any.whl (5.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.8 MB 7.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (1.8.1)\n",
            "Requirement already satisfied: numpy>=1.12.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (1.21.5)\n",
            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (1.35.0)\n",
            "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (1.0.0)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (0.4.6)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (1.0.1)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (3.3.6)\n",
            "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (0.6.1)\n",
            "Requirement already satisfied: protobuf>=3.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (3.19.4)\n",
            "Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (0.37.1)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (2.27.1)\n",
            "Requirement already satisfied: grpcio>=1.24.3 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (1.44.0)\n",
            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard) (57.4.0)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from absl-py>=0.4->tensorboard) (1.15.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tensorboard) (4.8)\n",
            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tensorboard) (4.2.4)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tensorboard) (0.2.8)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard) (1.3.1)\n",
            "Requirement already satisfied: importlib-metadata>=4.4 in /usr/local/lib/python3.7/dist-packages (from markdown>=2.6.8->tensorboard) (4.11.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard) (3.7.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard) (3.10.0.2)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.7/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard) (0.4.8)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard) (2.0.12)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard) (2021.10.8)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard) (2.10)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard) (1.24.3)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard) (3.2.0)\n",
            "Installing collected packages: tensorboard\n",
            "Successfully installed tensorboard-2.8.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "tensorboard"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ns-iuQzXguxC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "71e09dd3-42b8-44d3-a068-7ba501f03e92"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found existing installation: opencv-python-headless 4.5.5.64\n",
            "Uninstalling opencv-python-headless-4.5.5.64:\n",
            "  Would remove:\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/*\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless-4.5.5.64.dist-info/*\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libavcodec-65fa80df.so.58.134.100\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libavformat-8ef5c7db.so.58.76.100\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libavutil-9c768859.so.56.70.100\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libbz2-a273e504.so.1.0.6\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libcrypto-09fe7800.so.1.1\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libgfortran-91cc3cb1.so.3.0.0\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libopenblas-r0-f650aae0.3.3.so\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libquadmath-96973f99.so.0.0.0\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libssl-b92f8066.so.1.1\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libswresample-99364a1c.so.3.9.100\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libswscale-e6451464.so.5.9.100\n",
            "    /usr/local/lib/python3.7/dist-packages/opencv_python_headless.libs/libvpx-1016051d.so.7.0.0\n",
            "  Would not remove (might be manually added):\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libQtCore-bbdab771.so.4.8.7\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libQtGui-903938cd.so.4.8.7\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libQtTest-1183da5d.so.4.8.7\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libavcodec-3cdd3bd4.so.58.62.100\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libavformat-69a63b50.so.58.35.100\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libavutil-8e8979a8.so.56.36.100\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libbz2-7225278b.so.1.0.3\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libcrypto-a25ff511.so.1.1\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libssl-fdf0b66c.so.1.1\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libswresample-c6b3bbb9.so.3.6.100\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libswscale-2d19f7d1.so.5.6.100\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libvpx-c887ea55.so.6.1.0\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/.libs/libz-a147dcb0.so.1.2.3\n",
            "    /usr/local/lib/python3.7/dist-packages/cv2/cv2.cpython-37m-x86_64-linux-gnu.so\n",
            "Proceed (y/n)? y\n",
            "  Successfully uninstalled opencv-python-headless-4.5.5.64\n",
            "Collecting opencv-python-headless==4.1.2.30\n",
            "  Downloading opencv_python_headless-4.1.2.30-cp37-cp37m-manylinux1_x86_64.whl (21.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 21.8 MB 1.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.14.5 in /usr/local/lib/python3.7/dist-packages (from opencv-python-headless==4.1.2.30) (1.21.5)\n",
            "Installing collected packages: opencv-python-headless\n",
            "Successfully installed opencv-python-headless-4.1.2.30\n"
          ]
        }
      ],
      "source": [
        "!pip uninstall opencv-python-headless==4.5.5.62 \n",
        "!pip install opencv-python-headless==4.1.2.30"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python model_main_tf2.py --model_dir=models/my_ssd_resnet50_v1_fpn --pipeline_config_path=models/my_ssd_resnet50_v1_fpn/pipeline.config --checkpoint_dir=models/my_ssd_resnet50_v1_fpn"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4EwOdy95n0nB",
        "outputId": "af785899-f8c4-4ea8-baea-be2cf7c252bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.\n",
            "W0323 18:27:38.544703 140402618234752 model_lib_v2.py:1090] Forced number of epochs for all eval validations to be 1.\n",
            "INFO:tensorflow:Maybe overwriting sample_1_of_n_eval_examples: None\n",
            "I0323 18:27:38.544917 140402618234752 config_util.py:552] Maybe overwriting sample_1_of_n_eval_examples: None\n",
            "INFO:tensorflow:Maybe overwriting use_bfloat16: False\n",
            "I0323 18:27:38.545004 140402618234752 config_util.py:552] Maybe overwriting use_bfloat16: False\n",
            "INFO:tensorflow:Maybe overwriting eval_num_epochs: 1\n",
            "I0323 18:27:38.545089 140402618234752 config_util.py:552] Maybe overwriting eval_num_epochs: 1\n",
            "WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
            "W0323 18:27:38.545207 140402618234752 model_lib_v2.py:1111] Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
            "2022-03-23 18:27:39.280854: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
            "INFO:tensorflow:Reading unweighted datasets: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "I0323 18:27:39.310845 140402618234752 dataset_builder.py:163] Reading unweighted datasets: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "INFO:tensorflow:Reading record datasets for input file: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "I0323 18:27:39.311083 140402618234752 dataset_builder.py:80] Reading record datasets for input file: ['/content/tensorflow2/workspace/training_demo/annotations/train.record']\n",
            "INFO:tensorflow:Number of filenames to read: 1\n",
            "I0323 18:27:39.311170 140402618234752 dataset_builder.py:81] Number of filenames to read: 1\n",
            "WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.\n",
            "W0323 18:27:39.311240 140402618234752 dataset_builder.py:88] num_readers has been reduced to 1 to match input file shards.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
            "W0323 18:27:39.313116 140402618234752 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.map()\n",
            "W0323 18:27:39.332848 140402618234752 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.map()\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
            "W0323 18:27:43.316993 140402618234752 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "W0323 18:27:44.466501 140402618234752 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "INFO:tensorflow:Waiting for new checkpoint at models/my_ssd_resnet50_v1_fpn\n",
            "I0323 18:27:46.934109 140402618234752 checkpoint_utils.py:136] Waiting for new checkpoint at models/my_ssd_resnet50_v1_fpn\n",
            "INFO:tensorflow:Found new checkpoint at models/my_ssd_resnet50_v1_fpn/ckpt-11\n",
            "I0323 18:27:46.935139 140402618234752 checkpoint_utils.py:145] Found new checkpoint at models/my_ssd_resnet50_v1_fpn/ckpt-11\n",
            "/usr/local/lib/python3.7/dist-packages/keras/backend.py:450: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
            "  warnings.warn('`tf.keras.backend.set_learning_phase` is deprecated and '\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "W0323 18:28:12.443416 140402618234752 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "INFO:tensorflow:Finished eval step 0\n",
            "I0323 18:28:12.554004 140402618234752 model_lib_v2.py:966] Finished eval step 0\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "tf.py_func is deprecated in TF V2. Instead, there are two\n",
            "    options available in V2.\n",
            "    - tf.py_function takes a python function which manipulates tf eager\n",
            "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
            "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
            "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
            "    being differentiable using a gradient tape.\n",
            "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
            "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
            "    stateful argument making all functions stateful.\n",
            "    \n",
            "W0323 18:28:12.685766 140402618234752 deprecation.py:343] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "tf.py_func is deprecated in TF V2. Instead, there are two\n",
            "    options available in V2.\n",
            "    - tf.py_function takes a python function which manipulates tf eager\n",
            "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
            "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
            "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
            "    being differentiable using a gradient tape.\n",
            "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
            "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
            "    stateful argument making all functions stateful.\n",
            "    \n",
            "INFO:tensorflow:Finished eval step 100\n",
            "I0323 18:28:21.223139 140402618234752 model_lib_v2.py:966] Finished eval step 100\n",
            "INFO:tensorflow:Finished eval step 200\n",
            "I0323 18:28:29.227863 140402618234752 model_lib_v2.py:966] Finished eval step 200\n",
            "INFO:tensorflow:Finished eval step 300\n",
            "I0323 18:28:37.553700 140402618234752 model_lib_v2.py:966] Finished eval step 300\n",
            "INFO:tensorflow:Finished eval step 400\n",
            "I0323 18:28:45.736449 140402618234752 model_lib_v2.py:966] Finished eval step 400\n",
            "INFO:tensorflow:Finished eval step 500\n",
            "I0323 18:28:53.824236 140402618234752 model_lib_v2.py:966] Finished eval step 500\n",
            "INFO:tensorflow:Finished eval step 600\n",
            "I0323 18:29:01.774771 140402618234752 model_lib_v2.py:966] Finished eval step 600\n",
            "INFO:tensorflow:Performing evaluation on 697 images.\n",
            "I0323 18:29:09.399530 140402618234752 coco_evaluation.py:293] Performing evaluation on 697 images.\n",
            "creating index...\n",
            "index created!\n",
            "INFO:tensorflow:Loading and preparing annotation results...\n",
            "I0323 18:29:09.401751 140402618234752 coco_tools.py:116] Loading and preparing annotation results...\n",
            "INFO:tensorflow:DONE (t=0.03s)\n",
            "I0323 18:29:09.436120 140402618234752 coco_tools.py:138] DONE (t=0.03s)\n",
            "creating index...\n",
            "index created!\n",
            "Running per image evaluation...\n",
            "Evaluate annotation type *bbox*\n",
            "DONE (t=3.43s).\n",
            "Accumulating evaluation results...\n",
            "DONE (t=0.65s).\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.051\n",
            " Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.152\n",
            " Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.020\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.002\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.010\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.110\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.105\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.213\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.336\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.007\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.230\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.539\n",
            "INFO:tensorflow:Eval metrics at step 10000\n",
            "I0323 18:29:13.574269 140402618234752 model_lib_v2.py:1015] Eval metrics at step 10000\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Precision/mAP: 0.051451\n",
            "I0323 18:29:13.628566 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Precision/mAP: 0.051451\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Precision/mAP@.50IOU: 0.151950\n",
            "I0323 18:29:13.630092 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Precision/mAP@.50IOU: 0.151950\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Precision/mAP@.75IOU: 0.020072\n",
            "I0323 18:29:13.631416 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Precision/mAP@.75IOU: 0.020072\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Precision/mAP (small): 0.001516\n",
            "I0323 18:29:13.632632 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Precision/mAP (small): 0.001516\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Precision/mAP (medium): 0.010249\n",
            "I0323 18:29:13.633863 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Precision/mAP (medium): 0.010249\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Precision/mAP (large): 0.109559\n",
            "I0323 18:29:13.635047 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Precision/mAP (large): 0.109559\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Recall/AR@1: 0.105105\n",
            "I0323 18:29:13.636309 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Recall/AR@1: 0.105105\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Recall/AR@10: 0.212764\n",
            "I0323 18:29:13.637598 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Recall/AR@10: 0.212764\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Recall/AR@100: 0.335738\n",
            "I0323 18:29:13.638838 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Recall/AR@100: 0.335738\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Recall/AR@100 (small): 0.007438\n",
            "I0323 18:29:13.640036 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Recall/AR@100 (small): 0.007438\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Recall/AR@100 (medium): 0.229870\n",
            "I0323 18:29:13.641221 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Recall/AR@100 (medium): 0.229870\n",
            "INFO:tensorflow:\t+ DetectionBoxes_Recall/AR@100 (large): 0.539494\n",
            "I0323 18:29:13.642439 140402618234752 model_lib_v2.py:1018] \t+ DetectionBoxes_Recall/AR@100 (large): 0.539494\n",
            "INFO:tensorflow:\t+ Loss/localization_loss: 0.512449\n",
            "I0323 18:29:13.643445 140402618234752 model_lib_v2.py:1018] \t+ Loss/localization_loss: 0.512449\n",
            "INFO:tensorflow:\t+ Loss/classification_loss: 0.600573\n",
            "I0323 18:29:13.644439 140402618234752 model_lib_v2.py:1018] \t+ Loss/classification_loss: 0.600573\n",
            "INFO:tensorflow:\t+ Loss/regularization_loss: 0.482740\n",
            "I0323 18:29:13.645395 140402618234752 model_lib_v2.py:1018] \t+ Loss/regularization_loss: 0.482740\n",
            "INFO:tensorflow:\t+ Loss/total_loss: 1.595763\n",
            "I0323 18:29:13.646437 140402618234752 model_lib_v2.py:1018] \t+ Loss/total_loss: 1.595763\n",
            "INFO:tensorflow:Exiting evaluation at step 10000\n",
            "I0323 18:29:13.813236 140402618234752 model_lib_v2.py:1169] Exiting evaluation at step 10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!tensorboard --logdir=models/my_ssd_resnet50_v1_fpn"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IcNNsucLr8Yg",
        "outputId": "44816919-fac8-46d5-8c6d-27c63c1f5f62"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "NOTE: Using experimental fast data loading logic. To disable, pass\n",
            "    \"--load_fast=false\" and report issues on GitHub. More details:\n",
            "    https://github.com/tensorflow/tensorboard/issues/4784\n",
            "\n",
            "Serving TensorBoard on localhost; to expose to the network, use a proxy or pass --bind_all\n",
            "TensorBoard 2.8.0 at http://localhost:6006/ (Press CTRL+C to quit)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pwd"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "g53BKL-d_KPX",
        "outputId": "fe0d279d-2eea-4102-be88-92ca5d69e6e9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/tensorflow2/workspace/training_demo'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python \\exporter_main_v2.py --input_type image_tensor --pipeline_config_path \\models\\my_ssd_resnet50_v1_fpn\\pipeline.config --trained_checkpoint_dir \\models\\my_ssd_resnet50_v1_fpn\\ --output_directory \\exported-models\\my_model"
      ],
      "metadata": {
        "id": "aMoyrfgl9xkJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e818461d-b9b9-4d39-e06c-f6ffeac64092"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "FATAL Flags parsing error: flag --output_directory=None: Flag --output_directory must have a value other than None.\n",
            "Pass --helpshort or --helpfull to see help on flags.\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "car_damage_detection_1.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOxAeAkzNr58aarF9tBvzZU",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "nbformat": 4,
  "nbformat_minor": 0
}