Sign_Language_detection_SSD_Mobilenet_Colab_TFLITE.ipynb

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  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "Copy of Roboflow-TensorFlow2-Object-Detection.ipynb",
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    "kernelspec": {
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  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "OGrQEZVFksmW"
      },
      "source": [
        "!pip install tf-nightly"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TUYfHJgWN-v7",
        "outputId": "2bac4f97-f863-4501-e44f-3f4b77c2a1bf"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive/', force_remount=True)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive/\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ypWGYdPlLRUN",
        "outputId": "a31d7751-5af6-4f0a-a76c-3cadb56582b0"
      },
      "source": [
        "import os\n",
        "import pathlib\n",
        "\n",
        "# Clone the tensorflow models repository if it doesn't already exist\n",
        "if \"models\" in pathlib.Path.cwd().parts:\n",
        "  while \"models\" in pathlib.Path.cwd().parts:\n",
        "    os.chdir('..')\n",
        "elif not pathlib.Path('models').exists():\n",
        "  !git clone --depth 1 https://github.com/tensorflow/models"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'models'...\n",
            "remote: Enumerating objects: 2578, done.\u001b[K\n",
            "remote: Counting objects: 100% (2578/2578), done.\u001b[K\n",
            "remote: Compressing objects: 100% (2149/2149), done.\u001b[K\n",
            "remote: Total 2578 (delta 641), reused 1273 (delta 397), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (2578/2578), 32.51 MiB | 35.45 MiB/s, done.\n",
            "Resolving deltas: 100% (641/641), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6QPmVBSlLTzM",
        "outputId": "c18cfde3-eb2b-478b-a2c1-7c7c4516ef69"
      },
      "source": [
        "# Install the Object Detection API\n",
        "%%bash\n",
        "cd models/research/\n",
        "protoc object_detection/protos/*.proto --python_out=.\n",
        "cp object_detection/packages/tf2/setup.py .\n",
        "python -m pip install .\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Processing /content/models/research\n",
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            "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~=2.4->tensorflow>=2.4.0->tf-models-official->object-detection==0.1) (3.1.0)\n",
            "Building wheels for collected packages: object-detection, avro-python3, future, dill, py-cpuinfo, seqeval\n",
            "  Building wheel for object-detection (setup.py): started\n",
            "  Building wheel for object-detection (setup.py): finished with status 'done'\n",
            "  Created wheel for object-detection: filename=object_detection-0.1-cp37-none-any.whl size=1643278 sha256=0047ee7cba46891b373265ddf6c77d42332eaa3de1c5c6dad62a416270e8d818\n",
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            "Successfully built object-detection avro-python3 future dill py-cpuinfo seqeval\n",
            "Installing collected packages: avro-python3, requests, pbr, mock, future, fastavro, hdfs, dill, pyarrow, apache-beam, tf-slim, lvis, py-cpuinfo, seqeval, sentencepiece, opencv-python-headless, pyyaml, tensorflow-model-optimization, dataclasses, tensorflow-addons, tf-models-official, object-detection\n",
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            "    Uninstalling requests-2.23.0:\n",
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            "      Successfully uninstalled PyYAML-3.13\n",
            "Successfully installed apache-beam-2.28.0 avro-python3-1.10.2 dataclasses-0.6 dill-0.3.1.1 fastavro-1.3.5 future-0.18.2 hdfs-2.6.0 lvis-0.5.3 mock-2.0.0 object-detection-0.1 opencv-python-headless-4.5.1.48 pbr-5.5.1 py-cpuinfo-7.0.0 pyarrow-2.0.0 pyyaml-5.4.1 requests-2.25.1 sentencepiece-0.1.95 seqeval-1.2.2 tensorflow-addons-0.12.1 tensorflow-model-optimization-0.5.0 tf-models-official-2.4.0 tf-slim-1.1.0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "ERROR: multiprocess 0.70.11.1 has requirement dill>=0.3.3, but you'll have dill 0.3.1.1 which is incompatible.\n",
            "ERROR: google-colab 1.0.0 has requirement requests~=2.23.0, but you'll have requests 2.25.1 which is incompatible.\n",
            "ERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\n",
            "ERROR: apache-beam 2.28.0 has requirement avro-python3!=1.9.2,<1.10.0,>=1.8.1, but you'll have avro-python3 1.10.2 which is incompatible.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ng1bPuuGF7_5"
      },
      "source": [
        "!mkdir /content/drive/MyDrive/SignLanguageMobilenetV2"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vjhZuAMUGpdr",
        "outputId": "e533f095-6da6-4dd3-ee68-d04d5f6b18db"
      },
      "source": [
        "#if the below link doesn't work Generate the data set from here \n",
        "# https://app.roboflow.com/dataset/american-sign-language-letters-14kx4/generate\n",
        "!curl -L \"https://app.roboflow.com/ds/Xm8xzbRAxk?key=ZMSy423z9F\" > /content/drive/MyDrive/SignLanguageMobilenetV2/roboflow.zip;"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "100   891  100   891    0     0   1143      0 --:--:-- --:--:-- --:--:--  1142\n",
            "100 10.3M  100 10.3M    0     0  8921k      0  0:00:01  0:00:01 --:--:-- 8921k\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IcN3HiluQwTg",
        "outputId": "4de8891b-4c8a-42ca-80c0-bcd307a37182"
      },
      "source": [
        "!mkdir /content/drive/MyDrive/SignLanguageMobilenetV2/data\n",
        "!unzip /content/drive/MyDrive/SignLanguageMobilenetV2/roboflow.zip -d /content/drive/MyDrive/SignLanguageMobilenetV2/data"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "mkdir: cannot create directory ‘/content/drive/MyDrive/SignLanguageMobilenetV2/data’: File exists\n",
            "Archive:  /content/drive/MyDrive/SignLanguageMobilenetV2/roboflow.zip\n",
            "replace /content/drive/MyDrive/SignLanguageMobilenetV2/data/README.roboflow.txt? [y]es, [n]o, [A]ll, [N]one, [r]ename: Y\n",
            " extracting: /content/drive/MyDrive/SignLanguageMobilenetV2/data/README.roboflow.txt  \n",
            "replace /content/drive/MyDrive/SignLanguageMobilenetV2/data/test/Letters.tfrecord? [y]es, [n]o, [A]ll, [N]one, [r]ename: A\n",
            " extracting: /content/drive/MyDrive/SignLanguageMobilenetV2/data/test/Letters.tfrecord  \n",
            " extracting: /content/drive/MyDrive/SignLanguageMobilenetV2/data/test/Letters_label_map.pbtxt  \n",
            " extracting: /content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters.tfrecord  \n",
            " extracting: /content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters_label_map.pbtxt  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-rooksohdVSN"
      },
      "source": [
        "Y# NOTE: Update these TFRecord names from \"cells\" and \"cells_label_map\" to your files!\n",
        "test_record_fname = '/content/drive/MyDrive/SignLanguageMobilenetV2/data/valid/Letters.tfrecord'\n",
        "train_record_fname = '/content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters.tfrecord'\n",
        "label_map_pbtxt_fname = '/content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters_label_map.pbtxt'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gN0EUEa3e5Un"
      },
      "source": [
        "##change chosen model to deploy different models available in the TF2 object detection zoo\n",
        "MODELS_CONFIG = {\n",
        "    'ssd-mobilenet' : {\n",
        "        'model_name': 'ssd_mobilenet_v2',\n",
        "        'base_pipeline_file': 'ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.config',\n",
        "        'pretrained_checkpoint': 'ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.tar.gz',\n",
        "        'batch_size' : 16\n",
        "    },\n",
        "    'efficientdet-d0': {\n",
        "        'model_name': 'efficientdet_d0_coco17_tpu-32',\n",
        "        'base_pipeline_file': 'ssd_efficientdet_d0_512x512_coco17_tpu-8.config',\n",
        "        'pretrained_checkpoint': 'efficientdet_d0_coco17_tpu-32.tar.gz',\n",
        "        'batch_size': 16\n",
        "    },\n",
        "    'efficientdet-d1': {\n",
        "        'model_name': 'efficientdet_d1_coco17_tpu-32',\n",
        "        'base_pipeline_file': 'ssd_efficientdet_d1_640x640_coco17_tpu-8.config',\n",
        "        'pretrained_checkpoint': 'efficientdet_d1_coco17_tpu-32.tar.gz',\n",
        "        'batch_size': 16\n",
        "    },\n",
        "    'efficientdet-d2': {\n",
        "        'model_name': 'efficientdet_d2_coco17_tpu-32',\n",
        "        'base_pipeline_file': 'ssd_efficientdet_d2_768x768_coco17_tpu-8.config',\n",
        "        'pretrained_checkpoint': 'efficientdet_d2_coco17_tpu-32.tar.gz',\n",
        "        'batch_size': 16\n",
        "    },\n",
        "        'efficientdet-d3': {\n",
        "        'model_name': 'efficientdet_d3_coco17_tpu-32',\n",
        "        'base_pipeline_file': 'ssd_efficientdet_d3_896x896_coco17_tpu-32.config',\n",
        "        'pretrained_checkpoint': 'efficientdet_d3_coco17_tpu-32.tar.gz',\n",
        "        'batch_size': 16\n",
        "    }\n",
        "}\n",
        "\n",
        "#in this tutorial we implement the lightweight, smallest state of the art efficientdet model\n",
        "#if you want to scale up tot larger efficientdet models you will likely need more compute!\n",
        "chosen_model = 'ssd-mobilenet'\n",
        "\n",
        "num_steps = 40000 #The more steps, the longer the training. Increase if your loss function is still decreasing and validation metrics are increasing. \n",
        "num_eval_steps = 500 #Perform evaluation after so many steps\n",
        "\n",
        "model_name = MODELS_CONFIG[chosen_model]['model_name']\n",
        "pretrained_checkpoint = MODELS_CONFIG[chosen_model]['pretrained_checkpoint']\n",
        "base_pipeline_file = MODELS_CONFIG[chosen_model]['base_pipeline_file']\n",
        "batch_size = MODELS_CONFIG[chosen_model]['batch_size'] #if you can fit a large batch in memory, it may speed up your training"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kG4TmJUVrYQ7",
        "outputId": "e22c6c69-e023-46d4-80ea-0eb23161688d"
      },
      "source": [
        "#download pretrained weights\n",
        "%cd /content/drive/MyDrive/SignLanguageMobilenetV2\n",
        "import tarfile\n",
        "download_tar = 'http://download.tensorflow.org/models/object_detection/tf2/20200711/' + pretrained_checkpoint\n",
        "\n",
        "!wget {download_tar}\n",
        "tar = tarfile.open(pretrained_checkpoint)\n",
        "tar.extractall()\n",
        "tar.close()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/MyDrive/SignLanguageMobilenetV2\n",
            "--2021-04-07 06:59:59--  http://download.tensorflow.org/models/object_detection/tf2/20200711/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.tar.gz\n",
            "Resolving download.tensorflow.org (download.tensorflow.org)... 172.217.15.80, 2607:f8b0:4004:810::2010\n",
            "Connecting to download.tensorflow.org (download.tensorflow.org)|172.217.15.80|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 20515344 (20M) [application/x-tar]\n",
            "Saving to: ‘ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.tar.gz’\n",
            "\n",
            "ssd_mobilenet_v2_fp 100%[===================>]  19.56M  89.3MB/s    in 0.2s    \n",
            "\n",
            "2021-04-07 07:00:00 (89.3 MB/s) - ‘ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.tar.gz’ saved [20515344/20515344]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c-nqYZtdtsgG",
        "outputId": "31531dbe-8e8e-44a7-a003-c5e233209b15"
      },
      "source": [
        "#download base training configuration file\n",
        "%cd /content/drive/MyDrive/SignLanguageMobilenetV2\n",
        "download_config = 'https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/configs/tf2/' + base_pipeline_file\n",
        "!wget {download_config}"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/MyDrive/SignLanguageMobilenetV2\n",
            "--2021-04-07 07:01:56--  https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/configs/tf2/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.config\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 4684 (4.6K) [text/plain]\n",
            "Saving to: ‘ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.config’\n",
            "\n",
            "ssd_mobilenet_v2_fp 100%[===================>]   4.57K  --.-KB/s    in 0.001s  \n",
            "\n",
            "2021-04-07 07:01:56 (5.73 MB/s) - ‘ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.config’ saved [4684/4684]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b_ki9jOqxn7V",
        "outputId": "20bf45b1-b18d-459c-a331-a633d9dd9f73"
      },
      "source": [
        "#prepare\n",
        "pipeline_fname = '/content/drive/MyDrive/SignLanguageMobilenetV2/' + base_pipeline_file\n",
        "fine_tune_checkpoint = '/content/drive/MyDrive/SignLanguageMobilenetV2/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/checkpoint/ckpt-0'\n",
        "\n",
        "def get_num_classes(pbtxt_fname):\n",
        "    from object_detection.utils import label_map_util\n",
        "    label_map = label_map_util.load_labelmap(pbtxt_fname)\n",
        "    categories = label_map_util.convert_label_map_to_categories(\n",
        "        label_map, max_num_classes=90, use_display_name=True)\n",
        "    category_index = label_map_util.create_category_index(categories)\n",
        "    return len(category_index.keys())\n",
        "num_classes = get_num_classes(label_map_pbtxt_fname)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Enabling eager execution\n",
            "INFO:tensorflow:Enabling v2 tensorshape\n",
            "INFO:tensorflow:Enabling resource variables\n",
            "INFO:tensorflow:Enabling tensor equality\n",
            "INFO:tensorflow:Enabling control flow v2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5eA5ht3_yukT",
        "outputId": "1842ca29-5cfb-441f-c708-9f693ac4c456"
      },
      "source": [
        "#write custom configuration file by slotting our dataset, model checkpoint, and training parameters into the base pipeline file\n",
        "\n",
        "import re\n",
        "\n",
        "%cd /content/drive/MyDrive/SignLanguageMobilenetV2\n",
        "print('writing custom configuration file')\n",
        "\n",
        "with open(pipeline_fname) as f:\n",
        "    s = f.read()\n",
        "with open('pipeline_file.config', 'w') as f:\n",
        "    \n",
        "    # fine_tune_checkpoint\n",
        "    s = re.sub('fine_tune_checkpoint: \".*?\"',\n",
        "               'fine_tune_checkpoint: \"{}\"'.format(fine_tune_checkpoint), s)\n",
        "    \n",
        "    # tfrecord files train and test.\n",
        "    s = re.sub(\n",
        "        '(input_path: \".*?)(PATH_TO_BE_CONFIGURED/train)(.*?\")', 'input_path: \"{}\"'.format(train_record_fname), s)\n",
        "    s = re.sub(\n",
        "        '(input_path: \".*?)(PATH_TO_BE_CONFIGURED/val)(.*?\")', 'input_path: \"{}\"'.format(test_record_fname), s)\n",
        "\n",
        "    # label_map_path\n",
        "    s = re.sub(\n",
        "        'label_map_path: \".*?\"', 'label_map_path: \"{}\"'.format(label_map_pbtxt_fname), s)\n",
        "\n",
        "    # Set training batch_size.\n",
        "    s = re.sub('batch_size: [0-9]+',\n",
        "               'batch_size: {}'.format(batch_size), s)\n",
        "\n",
        "    # Set training steps, num_steps\n",
        "    s = re.sub('num_steps: [0-9]+',\n",
        "               'num_steps: {}'.format(num_steps), s)\n",
        "    \n",
        "    # Set number of classes num_classes.\n",
        "    s = re.sub('num_classes: [0-9]+',\n",
        "               'num_classes: {}'.format(num_classes), s)\n",
        "    \n",
        "    #fine-tune checkpoint type\n",
        "    s = re.sub(\n",
        "        'fine_tune_checkpoint_type: \"classification\"', 'fine_tune_checkpoint_type: \"{}\"'.format('detection'), s)\n",
        "        \n",
        "    f.write(s)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/MyDrive/SignLanguageMobilenetV2\n",
            "writing custom configuration file\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HEsOLOMHzBqF",
        "outputId": "96fa7d59-20b5-46ae-e437-b2cb96753a30"
      },
      "source": [
        "%cat /content/drive/MyDrive/SignLanguageMobilenetV2/pipeline_file.config"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "# SSD with Mobilenet v2 FPN-lite (go/fpn-lite) feature extractor, shared box\n",
            "# predictor and focal loss (a mobile version of Retinanet).\n",
            "# Retinanet: see Lin et al, https://arxiv.org/abs/1708.02002\n",
            "# Trained on COCO, initialized from Imagenet classification checkpoint\n",
            "# Train on TPU-8\n",
            "#\n",
            "# Achieves 22.2 mAP on COCO17 Val\n",
            "\n",
            "model {\n",
            "  ssd {\n",
            "    inplace_batchnorm_update: true\n",
            "    freeze_batchnorm: false\n",
            "    num_classes: 26\n",
            "    box_coder {\n",
            "      faster_rcnn_box_coder {\n",
            "        y_scale: 10.0\n",
            "        x_scale: 10.0\n",
            "        height_scale: 5.0\n",
            "        width_scale: 5.0\n",
            "      }\n",
            "    }\n",
            "    matcher {\n",
            "      argmax_matcher {\n",
            "        matched_threshold: 0.5\n",
            "        unmatched_threshold: 0.5\n",
            "        ignore_thresholds: false\n",
            "        negatives_lower_than_unmatched: true\n",
            "        force_match_for_each_row: true\n",
            "        use_matmul_gather: true\n",
            "      }\n",
            "    }\n",
            "    similarity_calculator {\n",
            "      iou_similarity {\n",
            "      }\n",
            "    }\n",
            "    encode_background_as_zeros: true\n",
            "    anchor_generator {\n",
            "      multiscale_anchor_generator {\n",
            "        min_level: 3\n",
            "        max_level: 7\n",
            "        anchor_scale: 4.0\n",
            "        aspect_ratios: [1.0, 2.0, 0.5]\n",
            "        scales_per_octave: 2\n",
            "      }\n",
            "    }\n",
            "    image_resizer {\n",
            "      fixed_shape_resizer {\n",
            "        height: 320\n",
            "        width: 320\n",
            "      }\n",
            "    }\n",
            "    box_predictor {\n",
            "      weight_shared_convolutional_box_predictor {\n",
            "        depth: 128\n",
            "        class_prediction_bias_init: -4.6\n",
            "        conv_hyperparams {\n",
            "          activation: RELU_6,\n",
            "          regularizer {\n",
            "            l2_regularizer {\n",
            "              weight: 0.00004\n",
            "            }\n",
            "          }\n",
            "          initializer {\n",
            "            random_normal_initializer {\n",
            "              stddev: 0.01\n",
            "              mean: 0.0\n",
            "            }\n",
            "          }\n",
            "          batch_norm {\n",
            "            scale: true,\n",
            "            decay: 0.997,\n",
            "            epsilon: 0.001,\n",
            "          }\n",
            "        }\n",
            "        num_layers_before_predictor: 4\n",
            "        share_prediction_tower: true\n",
            "        use_depthwise: true\n",
            "        kernel_size: 3\n",
            "      }\n",
            "    }\n",
            "    feature_extractor {\n",
            "      type: 'ssd_mobilenet_v2_fpn_keras'\n",
            "      use_depthwise: true\n",
            "      fpn {\n",
            "        min_level: 3\n",
            "        max_level: 7\n",
            "        additional_layer_depth: 128\n",
            "      }\n",
            "      min_depth: 16\n",
            "      depth_multiplier: 1.0\n",
            "      conv_hyperparams {\n",
            "        activation: RELU_6,\n",
            "        regularizer {\n",
            "          l2_regularizer {\n",
            "            weight: 0.00004\n",
            "          }\n",
            "        }\n",
            "        initializer {\n",
            "          random_normal_initializer {\n",
            "            stddev: 0.01\n",
            "            mean: 0.0\n",
            "          }\n",
            "        }\n",
            "        batch_norm {\n",
            "          scale: true,\n",
            "          decay: 0.997,\n",
            "          epsilon: 0.001,\n",
            "        }\n",
            "      }\n",
            "      override_base_feature_extractor_hyperparams: true\n",
            "    }\n",
            "    loss {\n",
            "      classification_loss {\n",
            "        weighted_sigmoid_focal {\n",
            "          alpha: 0.25\n",
            "          gamma: 2.0\n",
            "        }\n",
            "      }\n",
            "      localization_loss {\n",
            "        weighted_smooth_l1 {\n",
            "        }\n",
            "      }\n",
            "      classification_weight: 1.0\n",
            "      localization_weight: 1.0\n",
            "    }\n",
            "    normalize_loss_by_num_matches: true\n",
            "    normalize_loc_loss_by_codesize: true\n",
            "    post_processing {\n",
            "      batch_non_max_suppression {\n",
            "        score_threshold: 1e-8\n",
            "        iou_threshold: 0.6\n",
            "        max_detections_per_class: 100\n",
            "        max_total_detections: 100\n",
            "      }\n",
            "      score_converter: SIGMOID\n",
            "    }\n",
            "  }\n",
            "}\n",
            "\n",
            "train_config: {\n",
            "  fine_tune_checkpoint_version: V2\n",
            "  fine_tune_checkpoint: \"/content/drive/MyDrive/SignLanguageMobilenetV2/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/checkpoint/ckpt-0\"\n",
            "  fine_tune_checkpoint_type: \"detection\"\n",
            "  batch_size: 16\n",
            "  sync_replicas: true\n",
            "  startup_delay_steps: 0\n",
            "  replicas_to_aggregate: 8\n",
            "  num_steps: 40000\n",
            "  data_augmentation_options {\n",
            "    random_horizontal_flip {\n",
            "    }\n",
            "  }\n",
            "  data_augmentation_options {\n",
            "    random_crop_image {\n",
            "      min_object_covered: 0.0\n",
            "      min_aspect_ratio: 0.75\n",
            "      max_aspect_ratio: 3.0\n",
            "      min_area: 0.75\n",
            "      max_area: 1.0\n",
            "      overlap_thresh: 0.0\n",
            "    }\n",
            "  }\n",
            "  optimizer {\n",
            "    momentum_optimizer: {\n",
            "      learning_rate: {\n",
            "        cosine_decay_learning_rate {\n",
            "          learning_rate_base: .08\n",
            "          total_steps: 50000\n",
            "          warmup_learning_rate: .026666\n",
            "          warmup_steps: 1000\n",
            "        }\n",
            "      }\n",
            "      momentum_optimizer_value: 0.9\n",
            "    }\n",
            "    use_moving_average: false\n",
            "  }\n",
            "  max_number_of_boxes: 100\n",
            "  unpad_groundtruth_tensors: false\n",
            "}\n",
            "\n",
            "train_input_reader: {\n",
            "  label_map_path: \"/content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters_label_map.pbtxt\"\n",
            "  tf_record_input_reader {\n",
            "    input_path: \"/content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters.tfrecord\"\n",
            "  }\n",
            "}\n",
            "\n",
            "eval_config: {\n",
            "  metrics_set: \"coco_detection_metrics\"\n",
            "  use_moving_averages: false\n",
            "}\n",
            "\n",
            "eval_input_reader: {\n",
            "  label_map_path: \"/content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters_label_map.pbtxt\"\n",
            "  shuffle: false\n",
            "  num_epochs: 1\n",
            "  tf_record_input_reader {\n",
            "    input_path: \"/content/drive/MyDrive/SignLanguageMobilenetV2/data/valid/Letters.tfrecord\"\n",
            "  }\n",
            "}\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GMlaN3rs3zLe"
      },
      "source": [
        "pipeline_file = '/content/drive/MyDrive/SignLanguageMobilenetV2/pipeline_file.config'\n",
        "model_dir = '/content/drive/MyDrive/SignLanguageMobilenetV2/training'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tQTfZChVzzpZ",
        "outputId": "40c81b91-6de7-4670-e897-9df339e69297"
      },
      "source": [
        "!python /content/models/research/object_detection/model_main_tf2.py \\\n",
        "    --pipeline_config_path={pipeline_file} \\\n",
        "    --model_dir={model_dir} \\\n",
        "    --alsologtostderr \\\n",
        "    --num_train_steps={num_steps} \\\n",
        "    --sample_1_of_n_eval_examples=1 \\\n",
        "    --num_eval_steps={num_eval_steps}"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Traceback (most recent call last):\n",
            "  File \"/content/models/research/object_detection/model_main_tf2.py\", line 113, in <module>\n",
            "    tf.compat.v1.app.run()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/tensorflow/python/platform/app.py\", line 40, in run\n",
            "    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/absl/app.py\", line 303, in run\n",
            "    _run_main(main, args)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/absl/app.py\", line 251, in _run_main\n",
            "    sys.exit(main(argv))\n",
            "  File \"/content/models/research/object_detection/model_main_tf2.py\", line 110, in main\n",
            "    record_summaries=FLAGS.record_summaries)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py\", line 667, in train_loop\n",
            "    loss = _dist_train_step(train_input_iter)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/def_function.py\", line 828, in __call__\n",
            "    result = self._call(*args, **kwds)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/def_function.py\", line 855, in _call\n",
            "    return self._stateless_fn(*args, **kwds)  # pylint: disable=not-callable\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py\", line 2943, in __call__\n",
            "    filtered_flat_args, captured_inputs=graph_function.captured_inputs)  # pylint: disable=protected-access\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py\", line 1919, in _call_flat\n",
            "    ctx, args, cancellation_manager=cancellation_manager))\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py\", line 560, in call\n",
            "    ctx=ctx)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py\", line 60, in quick_execute\n",
            "    inputs, attrs, num_outputs)\n",
            "KeyboardInterrupt\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9KNv1N_hUibE"
      },
      "source": [
        "#run model evaluation to obtain performance metrics\n",
        "#!python /content/models/research/object_detection/model_main_tf2.py \\\n",
        "    #--pipeline_config_path={pipeline_file} \\d\n",
        "    #--model_dir={model_dir} \\\n",
        "    #--checkpoint_dir={model_dir} \\\n",
        "#Not yet implemented for EfficientDet"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4Vk2146Ogil3"
      },
      "source": [
        "## Exporting a Trained Inference Graph\n",
        "Still to come for TF2 models, we will be updating this Colab notebook accordingly as the functionality is added. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vqaZ4v-vIuDl",
        "outputId": "e86363f8-ea5b-4f6e-db9f-1cb9a56ce449"
      },
      "source": [
        "#see where our model saved weights\n",
        "%ls '/content/drive/MyDrive/SignLanguageMobilenetV2/training'"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "checkpoint  ckpt-1.data-00000-of-00001  ckpt-1.index  \u001b[0m\u001b[01;34mtrain\u001b[0m/\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YnSEZIzl4M10",
        "outputId": "dfb03a99-389e-42d8-c591-5dd99152156c"
      },
      "source": [
        "#run conversion script\n",
        "import re\n",
        "import numpy as np\n",
        "\n",
        "output_directory = '/content/drive/MyDrive/SignLanguageMobilenetV2/fine_tuned_model'\n",
        "\n",
        "#place the model weights you would like to export here\n",
        "last_model_path = '/content/drive/MyDrive/SignLanguageMobilenetV2/training'\n",
        "print(last_model_path)\n",
        "!python /content/models/research/object_detection/exporter_main_v2.py \\\n",
        "    --trained_checkpoint_dir {last_model_path} \\\n",
        "    --output_directory {output_directory} \\\n",
        "    --pipeline_config_path {pipeline_file}"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/MyDrive/SignLanguageMobilenetV2/training\n",
            "2021-04-07 13:28:54.747570: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
            "2021-04-07 13:28:56.823630: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
            "2021-04-07 13:28:56.824499: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1\n",
            "2021-04-07 13:28:56.856433: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:56.857013: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
            "pciBusID: 0000:00:04.0 name: Tesla T4 computeCapability: 7.5\n",
            "coreClock: 1.59GHz coreCount: 40 deviceMemorySize: 14.75GiB deviceMemoryBandwidth: 298.08GiB/s\n",
            "2021-04-07 13:28:56.857051: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
            "2021-04-07 13:28:56.862299: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11\n",
            "2021-04-07 13:28:56.862382: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11\n",
            "2021-04-07 13:28:56.865618: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10\n",
            "2021-04-07 13:28:56.865927: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10\n",
            "2021-04-07 13:28:56.870846: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10\n",
            "2021-04-07 13:28:56.871421: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11\n",
            "2021-04-07 13:28:56.871598: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8\n",
            "2021-04-07 13:28:56.871698: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:56.872260: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:56.872792: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
            "2021-04-07 13:28:56.873252: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
            "2021-04-07 13:28:56.873380: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:56.874123: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
            "pciBusID: 0000:00:04.0 name: Tesla T4 computeCapability: 7.5\n",
            "coreClock: 1.59GHz coreCount: 40 deviceMemorySize: 14.75GiB deviceMemoryBandwidth: 298.08GiB/s\n",
            "2021-04-07 13:28:56.874166: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
            "2021-04-07 13:28:56.874202: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11\n",
            "2021-04-07 13:28:56.874229: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11\n",
            "2021-04-07 13:28:56.874251: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10\n",
            "2021-04-07 13:28:56.874271: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10\n",
            "2021-04-07 13:28:56.874291: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10\n",
            "2021-04-07 13:28:56.874309: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11\n",
            "2021-04-07 13:28:56.874328: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8\n",
            "2021-04-07 13:28:56.874409: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:56.874969: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:56.875497: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
            "2021-04-07 13:28:56.875543: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
            "2021-04-07 13:28:57.383909: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2021-04-07 13:28:57.383962: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
            "2021-04-07 13:28:57.383978: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
            "2021-04-07 13:28:57.384183: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:57.384830: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:57.385398: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:28:57.385900: 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",
            "2021-04-07 13:28:57.385949: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 13994 MB memory) -> physical GPU (device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5)\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/exporter_lib_v2.py:106: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with back_prop=False is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "back_prop=False is deprecated. Consider using tf.stop_gradient instead.\n",
            "Instead of:\n",
            "results = tf.map_fn(fn, elems, back_prop=False)\n",
            "Use:\n",
            "results = tf.nest.map_structure(tf.stop_gradient, tf.map_fn(fn, elems))\n",
            "W0407 13:28:57.526640 140435601500032 deprecation.py:604] From /usr/local/lib/python3.7/dist-packages/object_detection/exporter_lib_v2.py:106: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with back_prop=False is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "back_prop=False is deprecated. Consider using tf.stop_gradient instead.\n",
            "Instead of:\n",
            "results = tf.map_fn(fn, elems, back_prop=False)\n",
            "Use:\n",
            "results = tf.nest.map_structure(tf.stop_gradient, tf.map_fn(fn, elems))\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7fb94006ca90>, because it is not built.\n",
            "W0407 13:29:14.266658 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7fb94006ca90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5f03f10>, because it is not built.\n",
            "W0407 13:29:15.084069 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5f03f10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d62210>, because it is not built.\n",
            "W0407 13:29:15.084316 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d62210>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5dd2cd0>, because it is not built.\n",
            "W0407 13:29:15.084450 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5dd2cd0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5dd2090>, because it is not built.\n",
            "W0407 13:29:15.084551 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5dd2090>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e43e50>, because it is not built.\n",
            "W0407 13:29:15.084653 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e43e50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5ee9a10>, because it is not built.\n",
            "W0407 13:29:15.084759 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5ee9a10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5e43310>, because it is not built.\n",
            "W0407 13:29:15.084860 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5e43310>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5ee9c50>, because it is not built.\n",
            "W0407 13:29:15.084964 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5ee9c50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e50f50>, because it is not built.\n",
            "W0407 13:29:15.085065 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e50f50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5dd2350>, because it is not built.\n",
            "W0407 13:29:15.085165 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7fb8f5dd2350>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5dfbf90>, because it is not built.\n",
            "W0407 13:29:15.085266 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5dfbf90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5dfb310>, because it is not built.\n",
            "W0407 13:29:15.085371 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5dfb310>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb908139b90>, because it is not built.\n",
            "W0407 13:29:15.085473 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb908139b90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f835eb10>, because it is not built.\n",
            "W0407 13:29:15.085572 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f835eb10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e21050>, because it is not built.\n",
            "W0407 13:29:15.085664 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e21050>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5cf7f10>, because it is not built.\n",
            "W0407 13:29:15.085874 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5cf7f10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5f9c990>, because it is not built.\n",
            "W0407 13:29:15.086030 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5f9c990>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5f5b810>, because it is not built.\n",
            "W0407 13:29:15.086131 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5f5b810>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d82c10>, because it is not built.\n",
            "W0407 13:29:15.086228 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d82c10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f83e4e50>, because it is not built.\n",
            "W0407 13:29:15.086330 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f83e4e50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5ddff50>, because it is not built.\n",
            "W0407 13:29:15.086437 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5ddff50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d87a50>, because it is not built.\n",
            "W0407 13:29:15.086525 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d87a50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d87750>, because it is not built.\n",
            "W0407 13:29:15.086608 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d87750>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d4f350>, because it is not built.\n",
            "W0407 13:29:15.086695 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d4f350>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d4f210>, because it is not built.\n",
            "W0407 13:29:15.086789 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5d4f210>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d4f650>, because it is not built.\n",
            "W0407 13:29:15.086873 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d4f650>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f86d9690>, because it is not built.\n",
            "W0407 13:29:15.086954 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f86d9690>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d4fed0>, because it is not built.\n",
            "W0407 13:29:15.087180 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5d4fed0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5f90dd0>, because it is not built.\n",
            "W0407 13:29:15.087290 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5f90dd0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e50850>, because it is not built.\n",
            "W0407 13:29:15.087411 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e50850>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5c51190>, because it is not built.\n",
            "W0407 13:29:15.087511 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5c51190>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5dd2390>, because it is not built.\n",
            "W0407 13:29:15.087613 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5dd2390>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5cf5590>, because it is not built.\n",
            "W0407 13:29:15.087706 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5cf5590>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5c51910>, because it is not built.\n",
            "W0407 13:29:15.087822 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5c51910>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5df4590>, because it is not built.\n",
            "W0407 13:29:15.087921 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5df4590>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5c51c50>, because it is not built.\n",
            "W0407 13:29:15.088027 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5c51c50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5c077d0>, because it is not built.\n",
            "W0407 13:29:15.088124 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5c077d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb90803b2d0>, because it is not built.\n",
            "W0407 13:29:15.088227 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb90803b2d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f82a4890>, because it is not built.\n",
            "W0407 13:29:15.088330 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f82a4890>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e0f9d0>, because it is not built.\n",
            "W0407 13:29:15.088441 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e0f9d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e2b190>, because it is not built.\n",
            "W0407 13:29:15.088543 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e2b190>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e64cd0>, because it is not built.\n",
            "W0407 13:29:15.088652 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5e64cd0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e64ad0>, because it is not built.\n",
            "W0407 13:29:15.139799 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7fb8f5e64ad0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5edd490>, because it is not built.\n",
            "W0407 13:29:15.139979 140435601500032 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7fb8f5edd490>, because it is not built.\n",
            "2021-04-07 13:29:24.882425: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:34.433777 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:34.434101 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:34.434366 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:34.434574 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:38.911986 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:38.912280 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:38.912499 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:38.912676 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:38.912863 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:38.913032 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "W0407 13:29:42.388071 140435601500032 save.py:241] Found untraced functions such as WeightSharedConvolutionalBoxPredictor_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxPredictor_layer_call_fn, WeightSharedConvolutionalBoxHead_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxHead_layer_call_fn, WeightSharedConvolutionalBoxPredictor_layer_call_fn while saving (showing 5 of 155). These functions will not be directly callable after loading.\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:42.592535 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:42.592845 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:42.593055 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:42.593230 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:42.861689 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:42.862108 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:42.862425 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:42.862675 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:42.862961 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:42.863228 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "W0407 13:29:43.380378 140435601500032 save.py:241] Found untraced functions such as WeightSharedConvolutionalBoxPredictor_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxPredictor_layer_call_fn, WeightSharedConvolutionalBoxHead_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxHead_layer_call_fn, WeightSharedConvolutionalBoxPredictor_layer_call_fn while saving (showing 5 of 155). These functions will not be directly callable after loading.\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:47.354555 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f250>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122f790>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f122fa50>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:47.354860 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11df8d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11dff10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11e2110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "I0407 13:29:47.355269 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119dd50>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f119df50>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11a5590>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
            "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "I0407 13:29:47.355495 140435601500032 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b48d0>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b4f10>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x7fb8f11b8110>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
            "INFO:tensorflow:Assets written to: /content/drive/MyDrive/SignLanguageMobilenetV2/fine_tuned_model/saved_model/assets\n",
            "I0407 13:29:48.216031 140435601500032 builder_impl.py:775] Assets written to: /content/drive/MyDrive/SignLanguageMobilenetV2/fine_tuned_model/saved_model/assets\n",
            "INFO:tensorflow:Writing pipeline config file to /content/drive/MyDrive/SignLanguageMobilenetV2/fine_tuned_model/pipeline.config\n",
            "I0407 13:29:48.960515 140435601500032 config_util.py:254] Writing pipeline config file to /content/drive/MyDrive/SignLanguageMobilenetV2/fine_tuned_model/pipeline.config\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TsE_uVjlsz3u",
        "outputId": "fddff801-234a-4c07-9301-9b0597c468be"
      },
      "source": [
        "%ls '/content/drive/MyDrive/SignLanguageMobilenetV2/fine_tuned_model/saved_model/'"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[0m\u001b[01;34massets\u001b[0m/  saved_model.pb  \u001b[01;34mvariables\u001b[0m/\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0f6DTolSDfXs",
        "outputId": "21a347d8-dc7a-48ea-ddc4-428b136ca5fb"
      },
      "source": [
        "%ls '/content/drive/MyDrive/SignLanguageMobilenetV2/training/'"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "checkpoint  ckpt-1.data-00000-of-00001  ckpt-1.index  \u001b[0m\u001b[01;34mtrain\u001b[0m/\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5RI3iJY0e3TA",
        "outputId": "0c434b0f-3a84-400f-f090-f36ced0cdced"
      },
      "source": [
        "#exporting \n",
        "!python /content/models/research/object_detection/export_tflite_graph_tf2.py \\\n",
        " --pipeline_config_path {pipeline_file} \\\n",
        " --trained_checkpoint_dir {last_model_path} \\\n",
        " --output_directory /content/drive/MyDrive/SignLanguageMobilenetV2/output/exported_models/tflite_inference"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2021-04-07 13:34:54.863140: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
            "2021-04-07 13:34:56.602901: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1\n",
            "2021-04-07 13:34:56.638179: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2021-04-07 13:34:56.639032: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1734] Found device 0 with properties: \n",
            "pciBusID: 0000:00:04.0 name: Tesla T4 computeCapability: 7.5\n",
            "coreClock: 1.59GHz coreCount: 40 deviceMemorySize: 14.75GiB deviceMemoryBandwidth: 298.08GiB/s\n",
            "2021-04-07 13:34:56.639088: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
            "2021-04-07 13:34:56.643283: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11\n",
            "2021-04-07 13:34:56.643392: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11\n",
            "2021-04-07 13:34:56.645484: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10\n",
            "2021-04-07 13:34:56.646159: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10\n",
            "2021-04-07 13:34:56.646438: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcusolver.so.11'; dlerror: libcusolver.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia\n",
            "2021-04-07 13:34:56.647943: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11\n",
            "2021-04-07 13:34:56.648271: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8\n",
            "2021-04-07 13:34:56.648308: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1767] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.\n",
            "Skipping registering GPU devices...\n",
            "2021-04-07 13:34:56.648662: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
            "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
            "2021-04-07 13:34:56.648816: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2021-04-07 13:34:56.648842: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1264]      \n",
            "2021-04-07 13:35:03.331713: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2021-04-07 13:35:03.331766: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1264]      \n",
            "2021-04-07 13:35:03.359356: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2199995000 Hz\n",
            "2021-04-07 13:35:05.009914: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2021-04-07 13:35:05.009964: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1264]      \n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7f7aa0432f10>, because it is not built.\n",
            "W0407 13:35:05.594241 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7f7aa0432f10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7aa0302190>, because it is not built.\n",
            "W0407 13:35:05.721550 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7aa0302190>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725ae150>, because it is not built.\n",
            "W0407 13:35:05.721837 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725ae150>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72b3ee50>, because it is not built.\n",
            "W0407 13:35:05.721976 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72b3ee50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7a728de9d0>, because it is not built.\n",
            "W0407 13:35:05.722084 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7a728de9d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725aed90>, because it is not built.\n",
            "W0407 13:35:05.722198 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725aed90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72800750>, because it is not built.\n",
            "W0407 13:35:05.722299 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72800750>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7a729dff10>, because it is not built.\n",
            "W0407 13:35:05.722405 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7a729dff10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a726ba650>, because it is not built.\n",
            "W0407 13:35:05.722497 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a726ba650>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72535490>, because it is not built.\n",
            "W0407 13:35:05.722589 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72535490>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7a72aa9c50>, because it is not built.\n",
            "W0407 13:35:05.722692 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x7f7a72aa9c50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725355d0>, because it is not built.\n",
            "W0407 13:35:05.722782 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725355d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7aa00d96d0>, because it is not built.\n",
            "W0407 13:35:05.722872 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7aa00d96d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7aa0302f50>, because it is not built.\n",
            "W0407 13:35:05.722965 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7aa0302f50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72831250>, because it is not built.\n",
            "W0407 13:35:05.723076 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72831250>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a72cde4d0>, because it is not built.\n",
            "W0407 13:35:05.723223 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a72cde4d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7258cc90>, because it is not built.\n",
            "W0407 13:35:05.723322 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7258cc90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a729dfc90>, because it is not built.\n",
            "W0407 13:35:05.723435 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a729dfc90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a726eea10>, because it is not built.\n",
            "W0407 13:35:05.723530 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a726eea10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a726d8710>, because it is not built.\n",
            "W0407 13:35:05.723617 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a726d8710>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a729d86d0>, because it is not built.\n",
            "W0407 13:35:05.723709 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a729d86d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7aa0302f90>, because it is not built.\n",
            "W0407 13:35:05.723789 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7aa0302f90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7aa02faa10>, because it is not built.\n",
            "W0407 13:35:05.723869 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7aa02faa10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a72577650>, because it is not built.\n",
            "W0407 13:35:05.723948 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a72577650>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72577a50>, because it is not built.\n",
            "W0407 13:35:05.724027 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72577a50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7277a290>, because it is not built.\n",
            "W0407 13:35:05.724105 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7277a290>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7277af50>, because it is not built.\n",
            "W0407 13:35:05.724185 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7277af50>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a72b9b590>, because it is not built.\n",
            "W0407 13:35:05.724264 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a72b9b590>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72593cd0>, because it is not built.\n",
            "W0407 13:35:05.724362 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72593cd0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725e15d0>, because it is not built.\n",
            "W0407 13:35:05.724448 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725e15d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7255b350>, because it is not built.\n",
            "W0407 13:35:05.724530 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7255b350>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7294f510>, because it is not built.\n",
            "W0407 13:35:05.724611 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7294f510>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a729c9ed0>, because it is not built.\n",
            "W0407 13:35:05.724697 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a729c9ed0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a724b4510>, because it is not built.\n",
            "W0407 13:35:05.724776 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a724b4510>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a724b45d0>, because it is not built.\n",
            "W0407 13:35:05.724861 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a724b45d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a724b4690>, because it is not built.\n",
            "W0407 13:35:05.724944 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a724b4690>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7291fb90>, because it is not built.\n",
            "W0407 13:35:05.725027 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7291fb90>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7aa0302fd0>, because it is not built.\n",
            "W0407 13:35:05.725108 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7aa0302fd0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7254f7d0>, because it is not built.\n",
            "W0407 13:35:05.725189 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7254f7d0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7254f990>, because it is not built.\n",
            "W0407 13:35:05.725273 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7254f990>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7254ffd0>, because it is not built.\n",
            "W0407 13:35:05.725368 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a7254ffd0>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7254f810>, because it is not built.\n",
            "W0407 13:35:05.725451 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a7254f810>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72676f10>, because it is not built.\n",
            "W0407 13:35:05.725532 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a72676f10>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725fd110>, because it is not built.\n",
            "W0407 13:35:05.725611 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x7f7a725fd110>, because it is not built.\n",
            "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a725fd490>, because it is not built.\n",
            "W0407 13:35:05.776879 140166648768384 save_impl.py:77] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x7f7a725fd490>, because it is not built.\n",
            "2021-04-07 13:35:14.457427: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.\n",
            "2021-04-07 13:35:15.963892: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2021-04-07 13:35:15.963945: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1264]      \n",
            "W0407 13:35:30.009474 140166648768384 save.py:243] Found untraced functions such as WeightSharedConvolutionalBoxPredictor_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxPredictor_layer_call_fn, WeightSharedConvolutionalBoxHead_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxHead_layer_call_fn, WeightSharedConvolutionalBoxPredictor_layer_call_fn while saving (showing 5 of 260). These functions will not be directly callable after loading.\n",
            "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/utils/generic_utils.py:497: CustomMaskWarning: Custom mask layers require a config and must override get_config. When loading, the custom mask layer must be passed to the custom_objects argument.\n",
            "  category=CustomMaskWarning)\n",
            "WARNING:tensorflow:FOR KERAS USERS: The object that you are saving contains one or more Keras models or layers. If you are loading the SavedModel with `tf.keras.models.load_model`, continue reading (otherwise, you may ignore the following instructions). Please change your code to save with `tf.keras.models.save_model` or `model.save`, and confirm that the file \"keras.metadata\" exists in the export directory. In the future, Keras will only load the SavedModels that have this file. In other words, `tf.saved_model.save` will no longer write SavedModels that can be recovered as Keras models (this will apply in TF 2.5).\n",
            "\n",
            "FOR DEVS: If you are overwriting _tracking_metadata in your class, this property has been used to save metadata in the SavedModel. The metadta field will be deprecated soon, so please move the metadata to a different file.\n",
            "W0407 13:35:33.612377 140166648768384 save.py:1240] FOR KERAS USERS: The object that you are saving contains one or more Keras models or layers. If you are loading the SavedModel with `tf.keras.models.load_model`, continue reading (otherwise, you may ignore the following instructions). Please change your code to save with `tf.keras.models.save_model` or `model.save`, and confirm that the file \"keras.metadata\" exists in the export directory. In the future, Keras will only load the SavedModels that have this file. In other words, `tf.saved_model.save` will no longer write SavedModels that can be recovered as Keras models (this will apply in TF 2.5).\n",
            "\n",
            "FOR DEVS: If you are overwriting _tracking_metadata in your class, this property has been used to save metadata in the SavedModel. The metadta field will be deprecated soon, so please move the metadata to a different file.\n",
            "INFO:tensorflow:Assets written to: /content/drive/MyDrive/SignLanguageMobilenetV2/output/exported_models/tflite_inference/saved_model/assets\n",
            "I0407 13:35:33.993963 140166648768384 builder_impl.py:775] Assets written to: /content/drive/MyDrive/SignLanguageMobilenetV2/output/exported_models/tflite_inference/saved_model/assets\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HnAzlFbQfwHw"
      },
      "source": [
        "saved_tflite_inference = \"/content/drive/MyDrive/SignLanguageMobilenetV2/output/exported_models/tflite_inference/saved_model\"\n",
        "/content/drive/MyDrive/SignLanguageMobilenetV2/output/exported_models/tflite_inference/saved_model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OcwnZMUPgDYH"
      },
      "source": [
        "def representative_dataset():\n",
        "    for _ in range(100):\n",
        "      data = np.random.rand(1, 320, 320, 3)\n",
        "      yield [data.astype(np.float32)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_kmhe2BlgJFe"
      },
      "source": [
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "\n",
        "converter = tf.lite.TFLiteConverter.from_saved_model(saved_tflite_inference)\n",
        "converter.allow_custom_ops = True\n",
        "converter.optimizations = [tf.lite.Optimize.DEFAULT]\n",
        "converter.representative_dataset = representative_dataset\n",
        "converter.inference_input_type = tf.uint8  # or tf.uint8\n",
        "converter.inference_output_type = tf.uint8  # or tf.uint8\n",
        "tflite_quant_model = converter.convert()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true
        },
        "id": "x9hqSDfDgNMO"
      },
      "source": [
        "tf_lite_model_path_without_metadata = \"/content/drive/MyDrive/SignLanguageMobilenetV2/output/tflite/detect_without_metadata.tflite\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "_kIypulwgWAr",
        "outputId": "dc09b6c4-3033-47da-d4bc-37f5b61999b8"
      },
      "source": [
        "with tf.io.gfile.GFile(tf_lite_model_path_without_metadata, 'wb') as f:\n",
        "  f.write(tflite_quant_model)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NotFoundError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNotFoundError\u001b[0m                             Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-10-36a9a70b4373>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtf_lite_model_path_without_metadata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m   \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtflite_quant_model\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/tensorflow/python/lib/io/file_io.py\u001b[0m in \u001b[0;36mwrite\u001b[0;34m(self, file_content)\u001b[0m\n\u001b[1;32m    100\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfile_content\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    101\u001b[0m     \u001b[0;34m\"\"\"Writes file_content to the file. Appends to the end of the file.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 102\u001b[0;31m     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_prewrite_check\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    103\u001b[0m     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_writable_file\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcompat\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile_content\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    104\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/tensorflow/python/lib/io/file_io.py\u001b[0m in \u001b[0;36m_prewrite_check\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     86\u001b[0m                                            \"File isn't open for writing\")\n\u001b[1;32m     87\u001b[0m       self._writable_file = _pywrap_file_io.WritableFile(\n\u001b[0;32m---> 88\u001b[0;31m           compat.path_to_bytes(self.__name), compat.as_bytes(self.__mode))\n\u001b[0m\u001b[1;32m     89\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     90\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_prepare_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNotFoundError\u001b[0m: /content/drive/MyDrive/SignLanguageMobilenetV2/output/tflite/detect_without_metadata.tflite; No such file or directory"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZzcFnOSSg8b8"
      },
      "source": [
        "## Testing the Input and Output of model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cDlBqLIigbW-"
      },
      "source": [
        "import tensorflow as tf\n",
        "\n",
        "# Load TFLite model and allocate tensors.\n",
        "interpreter = tf.lite.Interpreter(model_path=tf_lite_model_path_without_metadata)\n",
        "\n",
        "print(interpreter.get_input_details()[0]['shape'])\n",
        "print(interpreter.get_input_details()[0]['dtype'])\n",
        "\n",
        "# Print output shape and type\n",
        "print(interpreter.get_output_details()[0]['shape'])\n",
        "print(interpreter.get_output_details()[0]['dtype'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D0jBkBRQhAZH"
      },
      "source": [
        "## Writing Metadata to model for android/ios deployment"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KzOdz9b_gbaU"
      },
      "source": [
        "''' Writing MetaData to TfLite Model '''\n",
        "\n",
        "from tflite_support.metadata_writers import object_detector\n",
        "from tflite_support.metadata_writers import writer_utils\n",
        "from tflite_support import metadata\n",
        "\n",
        "ObjectDetectorWriter = object_detector.MetadataWriter\n",
        "_MODEL_PATH = tf_lite_model_path_without_metadata\n",
        "_LABEL_FILE = \"/content/drive/MyDrive/SignLanguageMobilenetV2/data/train/Letters_label_map.pbtxt\"\n",
        "_SAVE_TO_PATH = \"/content/drive/MyDrive/SignLanguageMobilenetV2/output/tflite/detect_with_metadata.tflite\"\n",
        "\n",
        "writer = ObjectDetectorWriter.create_for_inference(\n",
        "    writer_utils.load_file(_MODEL_PATH), [127.5], [127.5], [_LABEL_FILE])\n",
        "writer_utils.save_file(writer.populate(), _SAVE_TO_PATH)\n",
        "\n",
        "# Verify the populated metadata and associated files.\n",
        "displayer = metadata.MetadataDisplayer.with_model_file(_SAVE_TO_PATH)\n",
        "print(\"Metadata populated:\")\n",
        "print(displayer.get_metadata_json())\n",
        "print(\"Associated file(s) populated:\")\n",
        "print(displayer.get_packed_associated_file_list())"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}