TensorRT.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "TensorRT.ipynb",
      "provenance": [],
      "toc_visible": true,
      "authorship_tag": "ABX9TyPG+VXCJ2eWdx3FBHxpkwvz",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/MinwooKim1202/Lego_sorting_machine/blob/master/TensorRT.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vQIroT7E3Isd"
      },
      "source": [
        "###라이브러리 임포트"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "88b7KN5yfbpA"
      },
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow.python.framework import graph_io\n",
        "from tensorflow.keras.models import load_model\n",
        "from tensorflow.python.compiler.tensorrt import trt_convert as trt\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X6WAFxah4C1e"
      },
      "source": [
        "### Tensorflow 버전 확인"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cdMrF_v7f9yB",
        "outputId": "fb5d28b7-a96e-4561-f064-4da1550f486e"
      },
      "source": [
        "print(\"Tensorflow version: \", tf.version.VERSION)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tensorflow version:  2.4.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OZifUWNZ4H10"
      },
      "source": [
        "###Keras Model Upload(h5)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": "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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "T648oGK7h7C1",
        "outputId": "dcac499d-3dca-4d50-9646-1facf3eeea94"
      },
      "source": [
        "from google.colab import files\n",
        "file_uploaded = files.upload()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-b832755d-1f59-42ed-ba15-fadf2466ddc2\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-b832755d-1f59-42ed-ba15-fadf2466ddc2\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving lego_sorter_v7.h5 to lego_sorter_v7.h5\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qSS36ikO4T4j"
      },
      "source": [
        "### Model 불러오기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TwtXeiILf_qC"
      },
      "source": [
        "model = load_model('lego_sorter_v7.h5')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q0XZfqPw4k1b"
      },
      "source": [
        "###libnvinfer5 라이브러리 설치"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9uMzTRDyjr3B",
        "outputId": "2d5b30de-4dba-4f13-cbd7-5ceb12871c00"
      },
      "source": [
        "%%bash\n",
        "wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb\n",
        "\n",
        "dpkg -i nvidia-machine-learning-repo-*.deb\n",
        "apt-get update\n",
        "\n",
        "sudo apt-get install libnvinfer5"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Selecting previously unselected package nvidia-machine-learning-repo-ubuntu1804.\n",
            "(Reading database ... 160706 files and directories currently installed.)\n",
            "Preparing to unpack nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb ...\n",
            "Unpacking nvidia-machine-learning-repo-ubuntu1804 (1.0.0-1) ...\n",
            "Setting up nvidia-machine-learning-repo-ubuntu1804 (1.0.0-1) ...\n",
            "Get:1 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic InRelease [15.9 kB]\n",
            "Hit:2 http://archive.ubuntu.com/ubuntu bionic InRelease\n",
            "Get:3 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]\n",
            "Hit:4 http://ppa.launchpad.net/cran/libgit2/ubuntu bionic InRelease\n",
            "Get:5 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB]\n",
            "Hit:6 http://ppa.launchpad.net/deadsnakes/ppa/ubuntu bionic InRelease\n",
            "Get:7 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease [21.3 kB]\n",
            "Ign:8 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  InRelease\n",
            "Hit:9 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Release\n",
            "Get:10 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]\n",
            "Ign:11 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease\n",
            "Get:12 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release [697 B]\n",
            "Get:13 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release.gpg [836 B]\n",
            "Get:14 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ InRelease [3,626 B]\n",
            "Get:15 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic/main Sources [1,767 kB]\n",
            "Get:16 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic/main amd64 Packages [904 kB]\n",
            "Get:17 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 Packages [2,183 kB]\n",
            "Get:18 http://archive.ubuntu.com/ubuntu bionic-updates/restricted amd64 Packages [452 kB]\n",
            "Get:19 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 Packages [2,583 kB]\n",
            "Get:20 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic/main amd64 Packages [41.5 kB]\n",
            "Ign:22 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Packages\n",
            "Get:22 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Packages [796 kB]\n",
            "Get:23 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ Packages [60.5 kB]\n",
            "Get:24 http://security.ubuntu.com/ubuntu bionic-security/restricted amd64 Packages [423 kB]\n",
            "Get:25 http://security.ubuntu.com/ubuntu bionic-security/main amd64 Packages [2,152 kB]\n",
            "Get:26 http://security.ubuntu.com/ubuntu bionic-security/universe amd64 Packages [1,412 kB]\n",
            "Fetched 13.1 MB in 3s (3,850 kB/s)\n",
            "Reading package lists...\n",
            "Reading package lists...\n",
            "Building dependency tree...\n",
            "Reading state information...\n",
            "The following package was automatically installed and is no longer required:\n",
            "  libnvidia-common-460\n",
            "Use 'sudo apt autoremove' to remove it.\n",
            "The following NEW packages will be installed:\n",
            "  libnvinfer5\n",
            "0 upgraded, 1 newly installed, 0 to remove and 72 not upgraded.\n",
            "Need to get 46.7 MB of archives.\n",
            "After this operation, 163 MB of additional disk space will be used.\n",
            "Get:1 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  libnvinfer5 5.1.5-1+cuda10.1 [46.7 MB]\n",
            "Fetched 46.7 MB in 3s (14.5 MB/s)\n",
            "Selecting previously unselected package libnvinfer5.\r\n",
            "(Reading database ... \r(Reading database ... 5%\r(Reading database ... 10%\r(Reading database ... 15%\r(Reading database ... 20%\r(Reading database ... 25%\r(Reading database ... 30%\r(Reading database ... 35%\r(Reading database ... 40%\r(Reading database ... 45%\r(Reading database ... 50%\r(Reading database ... 55%\r(Reading database ... 60%\r(Reading database ... 65%\r(Reading database ... 70%\r(Reading database ... 75%\r(Reading database ... 80%\r(Reading database ... 85%\r(Reading database ... 90%\r(Reading database ... 95%\r(Reading database ... 100%\r(Reading database ... 160709 files and directories currently installed.)\r\n",
            "Preparing to unpack .../libnvinfer5_5.1.5-1+cuda10.1_amd64.deb ...\r\n",
            "Unpacking libnvinfer5 (5.1.5-1+cuda10.1) ...\r\n",
            "Setting up libnvinfer5 (5.1.5-1+cuda10.1) ...\r\n",
            "Processing triggers for libc-bin (2.27-3ubuntu1.2) ...\r\n",
            "/sbin/ldconfig.real: /usr/local/lib/python3.7/dist-packages/ideep4py/lib/libmkldnn.so.0 is not a symbolic link\r\n",
            "\r\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "--2021-05-21 08:09:04--  https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb\n",
            "Resolving developer.download.nvidia.com (developer.download.nvidia.com)... 152.199.20.126\n",
            "Connecting to developer.download.nvidia.com (developer.download.nvidia.com)|152.199.20.126|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 2926 (2.9K) [application/x-deb]\n",
            "Saving to: ‘nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb’\n",
            "\n",
            "     0K ..                                                    100%  120M=0s\n",
            "\n",
            "2021-05-21 08:09:05 (120 MB/s) - ‘nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb’ saved [2926/2926]\n",
            "\n",
            "W: Target Packages (Packages) is configured multiple times in /etc/apt/sources.list.d/nvidia-machine-learning.list:1 and /etc/apt/sources.list.d/nvidia-ml.list:1\n",
            "W: Target Packages (Packages) is configured multiple times in /etc/apt/sources.list.d/nvidia-machine-learning.list:1 and /etc/apt/sources.list.d/nvidia-ml.list:1\n",
            "debconf: unable to initialize frontend: Dialog\n",
            "debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 1.)\n",
            "debconf: falling back to frontend: Readline\n",
            "debconf: unable to initialize frontend: Readline\n",
            "debconf: (This frontend requires a controlling tty.)\n",
            "debconf: falling back to frontend: Teletype\n",
            "dpkg-preconfigure: unable to re-open stdin: \n",
            "W: Target Packages (Packages) is configured multiple times in /etc/apt/sources.list.d/nvidia-machine-learning.list:1 and /etc/apt/sources.list.d/nvidia-ml.list:1\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kiBZKozJ4s9C"
      },
      "source": [
        "###TensorRT version 확인"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gVZDM_4RjwFz",
        "outputId": "52b0c08e-890f-4957-9bd9-83aacecb7f7b"
      },
      "source": [
        "# check TensorRT version\n",
        "print(\"TensorRT version: \")\n",
        "!dpkg -l | grep nvinfer"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "TensorRT version: \n",
            "ii  libnvinfer5                             5.1.5-1+cuda10.1                    amd64        TensorRT runtime libraries\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LYEct3Ei41CK"
      },
      "source": [
        "###GPU 사용 확인"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ktL3-qOOj2Gp",
        "outputId": "ad5d7ef7-42e8-49b5-cb7c-e893a77a1c87"
      },
      "source": [
        "from tensorflow.python.client import device_lib\n",
        "\n",
        "def check_tensor_core_gpu_present():\n",
        "    local_device_protos = device_lib.list_local_devices()\n",
        "    for line in local_device_protos:\n",
        "        if \"compute capability\" in str(line):\n",
        "            compute_capability = float(line.physical_device_desc.split(\"compute capability: \")[-1])\n",
        "            if compute_capability>=7.0:\n",
        "                return True\n",
        "    \n",
        "print(\"Tensor Core GPU Present:\", check_tensor_core_gpu_present())\n",
        "tensor_core_gpu = check_tensor_core_gpu_present()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tensor Core GPU Present: None\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D_nl7OfRj5HZ"
      },
      "source": [
        "from tensorflow.python.saved_model import tag_constants\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2G0QhsGz5Ik6"
      },
      "source": [
        "###Model 저장"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z0IE3PRzkU9G",
        "outputId": "050ba6c7-8924-4506-e6c3-174db82fa1aa"
      },
      "source": [
        "model.save('legoNet_v7') "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Assets written to: legoNet_v7/assets\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jKPHDqMj5L5h"
      },
      "source": [
        "### Model 저장 확인 및 정보 확인 \n",
        "<strong>(Outputs node 이름을 확인하자)</strong>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3UwvyyFzka_o",
        "outputId": "8bb4fd35-8f59-4dfd-ffca-3d125c7c72f4"
      },
      "source": [
        "!saved_model_cli show --all --dir legoNet_v7"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "MetaGraphDef with tag-set: 'serve' contains the following SignatureDefs:\n",
            "\n",
            "signature_def['__saved_model_init_op']:\n",
            "  The given SavedModel SignatureDef contains the following input(s):\n",
            "  The given SavedModel SignatureDef contains the following output(s):\n",
            "    outputs['__saved_model_init_op'] tensor_info:\n",
            "        dtype: DT_INVALID\n",
            "        shape: unknown_rank\n",
            "        name: NoOp\n",
            "  Method name is: \n",
            "\n",
            "signature_def['serving_default']:\n",
            "  The given SavedModel SignatureDef contains the following input(s):\n",
            "    inputs['conv2d_input'] tensor_info:\n",
            "        dtype: DT_FLOAT\n",
            "        shape: (-1, 88, 88, 1)\n",
            "        name: serving_default_conv2d_input:0\n",
            "  The given SavedModel SignatureDef contains the following output(s):\n",
            "    outputs['dense_1'] tensor_info:\n",
            "        dtype: DT_FLOAT\n",
            "        shape: (-1, 11)\n",
            "        name: StatefulPartitionedCall:0\n",
            "  Method name is: tensorflow/serving/predict\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/bin/saved_model_cli\", line 8, in <module>\n",
            "    sys.exit(main())\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tools/saved_model_cli.py\", line 990, in main\n",
            "    args.func(args)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tools/saved_model_cli.py\", line 691, in show\n",
            "    _show_all(args.dir)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tools/saved_model_cli.py\", line 283, in _show_all\n",
            "    _show_defined_functions(saved_model_dir)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tools/saved_model_cli.py\", line 176, in _show_defined_functions\n",
            "    trackable_object = load.load(saved_model_dir)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/saved_model/load.py\", line 528, in load\n",
            "    return load_internal(export_dir, tags)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/saved_model/load.py\", line 552, in load_internal\n",
            "    export_dir)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/saved_model/load.py\", line 114, in __init__\n",
            "    meta_graph.graph_def.library))\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/saved_model/function_deserialization.py\", line 312, in load_function_def_library\n",
            "    func_graph = function_def_lib.function_def_to_graph(copy)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/framework/function_def_to_graph.py\", line 63, in function_def_to_graph\n",
            "    importer.import_graph_def_for_function(graph_def, name=\"\")\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/framework/importer.py\", line 412, in import_graph_def_for_function\n",
            "    graph_def, validate_colocation_constraints=False, name=name)\n",
            "  File \"/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/framework/importer.py\", line 501, in _import_graph_def_internal\n",
            "    raise ValueError(str(e))\n",
            "ValueError: NodeDef mentions attr 'exponential_avg_factor' not in Op<name=FusedBatchNormV3; signature=x:T, scale:U, offset:U, mean:U, variance:U -> y:T, batch_mean:U, batch_variance:U, reserve_space_1:U, reserve_space_2:U, reserve_space_3:U; attr=T:type,allowed=[DT_HALF, DT_BFLOAT16, DT_FLOAT]; attr=U:type,allowed=[DT_FLOAT]; attr=epsilon:float,default=0.0001; attr=data_format:string,default=\"NHWC\",allowed=[\"NHWC\", \"NCHW\"]; attr=is_training:bool,default=true>; NodeDef: {{node FusedBatchNormV3}}. (Check whether your GraphDef-interpreting binary is up to date with your GraphDef-generating binary.).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O4SyCb0E5TVC"
      },
      "source": [
        "### <strong>FP16으로 변환</strong>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VTdx4nixkCqb",
        "outputId": "3e3caa74-5df9-4a3e-fd3a-7a79c6c65a6d"
      },
      "source": [
        "print('Converting to TF-TRT FP16...')\n",
        "conversion_params = trt.DEFAULT_TRT_CONVERSION_PARAMS._replace(\n",
        "    precision_mode=trt.TrtPrecisionMode.FP16,\n",
        "    max_workspace_size_bytes=8000000000)\n",
        "converter = trt.TrtGraphConverterV2(\n",
        "   input_saved_model_dir='legoNet_v7', conversion_params=conversion_params)\n",
        "converter.convert()\n",
        "converter.save(output_saved_model_dir='LegoNet_V7_FP16')\n",
        "print('Done Converting to TF-TRT FP16')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Converting to TF-TRT FP16...\n",
            "INFO:tensorflow:Linked TensorRT version: (0, 0, 0)\n",
            "INFO:tensorflow:Loaded TensorRT version: (0, 0, 0)\n",
            "INFO:tensorflow:Assets written to: LegoNet_V7_FP16/assets\n",
            "Done Converting to TF-TRT FP16\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FvZZHSrQ5ww6"
      },
      "source": [
        "### 압축파일 만들기\n",
        "왼쪽 파일탭에서 압축파일을 찾아서 다운로드 하면 끝!! "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HNSh6pmipHnK",
        "outputId": "55661014-83a4-4579-a550-8a641e11ca75"
      },
      "source": [
        "!tar -cvf TR_model.tar LegoNet_V7_FP16"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "LegoNet_V7_FP16/\n",
            "LegoNet_V7_FP16/variables/\n",
            "LegoNet_V7_FP16/variables/variables.index\n",
            "LegoNet_V7_FP16/variables/variables.data-00000-of-00001\n",
            "LegoNet_V7_FP16/saved_model.pb\n",
            "LegoNet_V7_FP16/assets/\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}