notebook.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JOUnWaWGKDRC"
      },
      "source": [
        "# Training traffic sign detector - TFS data centric\n",
        "\n",
        "Main repository: [https://github.com/makerviet/tfs-data-centric](https://github.com/makerviet/tfs-data-centric)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RSnwbR5SoJ9e"
      },
      "source": [
        "## 1. Prepare environment"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wM-sqTCWJXav",
        "outputId": "6abace65-472d-40c8-fd62-a606c0478b05"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Fri Aug  4 17:58:31 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.105.17   Driver Version: 525.105.17   CUDA Version: 12.0     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   42C    P8     9W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "# Check your GPU\n",
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EUtYUl3upAyw"
      },
      "source": [
        "Reinstall PyTorch to prevent errors on next steps."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "127IQXcUEgK7",
        "outputId": "dfc2b689-8487-49fc-cfaa-3b54a3c667d4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Found existing installation: torch 2.0.1\n",
            "Uninstalling torch-2.0.1:\n",
            "  Successfully uninstalled torch-2.0.1\n",
            "Found existing installation: torchvision 0.15.2\n",
            "Uninstalling torchvision-0.15.2:\n",
            "  Successfully uninstalled torchvision-0.15.2\n",
            "Found existing installation: torchtext 0.15.2\n",
            "Uninstalling torchtext-0.15.2:\n",
            "  Successfully uninstalled torchtext-0.15.2\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mCollecting torch==2.0.1\n",
            "  Using cached torch-2.0.1-cp310-cp310-manylinux1_x86_64.whl (619.9 MB)\n",
            "Collecting torchvision\n",
            "  Using cached torchvision-0.15.2-cp310-cp310-manylinux1_x86_64.whl (6.0 MB)\n",
            "Collecting torchtext\n",
            "  Using cached torchtext-0.15.2-cp310-cp310-manylinux1_x86_64.whl (2.0 MB)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (3.12.2)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (4.7.1)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (1.11.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (3.1.2)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (11.7.101)\n",
            "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (8.5.0.96)\n",
            "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (11.10.3.66)\n",
            "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (10.9.0.58)\n",
            "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (10.2.10.91)\n",
            "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (11.4.0.1)\n",
            "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (11.7.4.91)\n",
            "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (2.14.3)\n",
            "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (11.7.91)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (2.0.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch==2.0.1) (67.7.2)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch==2.0.1) (0.41.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch==2.0.1) (3.25.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch==2.0.1) (16.0.6)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torchvision) (1.22.4)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from torchvision) (2.27.1)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision) (9.4.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from torchtext) (4.65.0)\n",
            "Requirement already satisfied: torchdata==0.6.1 in /usr/local/lib/python3.10/dist-packages (from torchtext) (0.6.1)\n",
            "Requirement already satisfied: urllib3>=1.25 in /usr/local/lib/python3.10/dist-packages (from torchdata==0.6.1->torchtext) (1.26.16)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.0.1) (2.1.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision) (2023.7.22)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision) (3.4)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.0.1) (1.3.0)\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mInstalling collected packages: torch, torchvision, torchtext\n",
            "Successfully installed torch-2.0.1 torchtext-0.15.2 torchvision-0.15.2\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "!pip uninstall torch torchvision torchtext -y\n",
        "!pip install torch==2.0.1 torchvision torchtext"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8mwmz3F1CTMh"
      },
      "source": [
        "### Install training code\n",
        "\n",
        "Clone code and install environment:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2f8mb7krCs0Q",
        "outputId": "5aae7133-1f2e-4107-8de8-7d70b856c4cd"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content\n",
            "fatal: destination path 'tfs-data-centric' already exists and is not an empty directory.\n",
            "/content/tfs-data-centric\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mRequirement already satisfied: pip in /usr/local/lib/python3.10/dist-packages (23.2.1)\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 2)) (1.22.4)\n",
            "Requirement already satisfied: torch>=1.7 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 3)) (2.0.1)\n",
            "Requirement already satisfied: opencv_python in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 4)) (4.7.0.72)\n",
            "Requirement already satisfied: loguru in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 5)) (0.7.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 6)) (4.65.0)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 7)) (0.15.2)\n",
            "Requirement already satisfied: thop in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 8)) (0.1.1.post2209072238)\n",
            "Requirement already satisfied: ninja in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 9)) (1.11.1)\n",
            "Requirement already satisfied: tabulate in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 10)) (0.9.0)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 11)) (5.9.5)\n",
            "Requirement already satisfied: tensorboard in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 12)) (2.12.3)\n",
            "Requirement already satisfied: pycocotools>=2.0.2 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 16)) (2.0.6)\n",
            "Requirement already satisfied: onnx>=1.13.0 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 17)) (1.14.0)\n",
            "Requirement already satisfied: onnx-simplifier==0.4.10 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 18)) (0.4.10)\n",
            "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from onnx-simplifier==0.4.10->-r requirements.txt (line 18)) (13.4.2)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (3.12.2)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (4.7.1)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (1.11.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (3.1.2)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (11.7.101)\n",
            "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (8.5.0.96)\n",
            "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (11.10.3.66)\n",
            "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (10.9.0.58)\n",
            "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (10.2.10.91)\n",
            "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (11.4.0.1)\n",
            "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (11.7.4.91)\n",
            "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (2.14.3)\n",
            "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (11.7.91)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->-r requirements.txt (line 3)) (2.0.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.7->-r requirements.txt (line 3)) (67.7.2)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.7->-r requirements.txt (line 3)) (0.41.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.7->-r requirements.txt (line 3)) (3.25.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.7->-r requirements.txt (line 3)) (16.0.6)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from torchvision->-r requirements.txt (line 7)) (2.27.1)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision->-r requirements.txt (line 7)) (9.4.0)\n",
            "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (1.4.0)\n",
            "Requirement already satisfied: grpcio>=1.48.2 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (1.56.2)\n",
            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (2.17.3)\n",
            "Requirement already satisfied: google-auth-oauthlib<1.1,>=0.5 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (1.0.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (3.4.4)\n",
            "Requirement already satisfied: protobuf>=3.19.6 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (3.20.3)\n",
            "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (0.7.1)\n",
            "Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard->-r requirements.txt (line 12)) (2.3.6)\n",
            "Requirement already satisfied: matplotlib>=2.1.0 in /usr/local/lib/python3.10/dist-packages (from pycocotools>=2.0.2->-r requirements.txt (line 16)) (3.7.1)\n",
            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->-r requirements.txt (line 12)) (5.3.1)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->-r requirements.txt (line 12)) (0.3.0)\n",
            "Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->-r requirements.txt (line 12)) (1.16.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->-r requirements.txt (line 12)) (4.9)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<1.1,>=0.5->tensorboard->-r requirements.txt (line 12)) (1.3.1)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->-r requirements.txt (line 16)) (1.1.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->-r requirements.txt (line 16)) (0.11.0)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->-r requirements.txt (line 16)) (4.41.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->-r requirements.txt (line 16)) (1.4.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->-r requirements.txt (line 16)) (23.1)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->-r requirements.txt (line 16)) (3.1.0)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->-r requirements.txt (line 16)) (2.8.2)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->-r requirements.txt (line 7)) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->-r requirements.txt (line 7)) (2023.7.22)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->-r requirements.txt (line 7)) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->-r requirements.txt (line 7)) (3.4)\n",
            "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard->-r requirements.txt (line 12)) (2.1.3)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->onnx-simplifier==0.4.10->-r requirements.txt (line 18)) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->onnx-simplifier==0.4.10->-r requirements.txt (line 18)) (2.14.0)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.7->-r requirements.txt (line 3)) (1.3.0)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->onnx-simplifier==0.4.10->-r requirements.txt (line 18)) (0.1.2)\n",
            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard->-r requirements.txt (line 12)) (0.5.0)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<1.1,>=0.5->tensorboard->-r requirements.txt (line 12)) (3.2.2)\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0mUsing pip 23.2.1 from /usr/local/lib/python3.10/dist-packages/pip (python 3.10)\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mObtaining file:///content/tfs-data-centric\n",
            "  Running command python setup.py egg_info\n",
            "  /usr/local/lib/python3.10/dist-packages/setuptools/__init__.py:84: _DeprecatedInstaller: setuptools.installer and fetch_build_eggs are deprecated.\n",
            "  !!\n",
            "\n",
            "          ********************************************************************************\n",
            "          Requirements should be satisfied by a PEP 517 installer.\n",
            "          If you are using pip, you can try `pip install --use-pep517`.\n",
            "          ********************************************************************************\n",
            "\n",
            "  !!\n",
            "    dist.fetch_build_eggs(dist.setup_requires)\n",
            "  running egg_info\n",
            "  creating /tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info\n",
            "  writing /tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info/PKG-INFO\n",
            "  writing dependency_links to /tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info/dependency_links.txt\n",
            "  writing requirements to /tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info/requires.txt\n",
            "  writing top-level names to /tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info/top_level.txt\n",
            "  writing manifest file '/tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info/SOURCES.txt'\n",
            "  reading manifest file '/tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info/SOURCES.txt'\n",
            "  reading manifest template 'MANIFEST.in'\n",
            "  warning: no files found matching '*.cu' under directory 'yolox'\n",
            "  warning: no files found matching '*.cuh' under directory 'yolox'\n",
            "  warning: no files found matching '*.cc' under directory 'yolox'\n",
            "  writing manifest file '/tmp/pip-pip-egg-info-z5kbsxym/yolox.egg-info/SOURCES.txt'\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[33m  WARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (1.22.4)\n",
            "Requirement already satisfied: torch>=1.7 in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (2.0.1)\n",
            "Requirement already satisfied: opencv_python in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (4.7.0.72)\n",
            "Requirement already satisfied: loguru in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (0.7.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (4.65.0)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (0.15.2)\n",
            "Requirement already satisfied: thop in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (0.1.1.post2209072238)\n",
            "Requirement already satisfied: ninja in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (1.11.1)\n",
            "Requirement already satisfied: tabulate in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (0.9.0)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (5.9.5)\n",
            "Requirement already satisfied: tensorboard in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (2.12.3)\n",
            "Requirement already satisfied: pycocotools>=2.0.2 in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (2.0.6)\n",
            "Requirement already satisfied: onnx>=1.13.0 in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (1.14.0)\n",
            "Requirement already satisfied: onnx-simplifier==0.4.10 in /usr/local/lib/python3.10/dist-packages (from yolox==0.3.0) (0.4.10)\n",
            "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from onnx-simplifier==0.4.10->yolox==0.3.0) (13.4.2)\n",
            "Requirement already satisfied: protobuf>=3.20.2 in /usr/local/lib/python3.10/dist-packages (from onnx>=1.13.0->yolox==0.3.0) (3.20.3)\n",
            "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.10/dist-packages (from onnx>=1.13.0->yolox==0.3.0) (4.7.1)\n",
            "Requirement already satisfied: matplotlib>=2.1.0 in /usr/local/lib/python3.10/dist-packages (from pycocotools>=2.0.2->yolox==0.3.0) (3.7.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (3.12.2)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (1.11.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (3.1.2)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (11.7.101)\n",
            "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (8.5.0.96)\n",
            "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (11.10.3.66)\n",
            "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (10.9.0.58)\n",
            "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (10.2.10.91)\n",
            "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (11.4.0.1)\n",
            "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (11.7.4.91)\n",
            "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (2.14.3)\n",
            "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (11.7.91)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7->yolox==0.3.0) (2.0.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.7->yolox==0.3.0) (67.7.2)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.7->yolox==0.3.0) (0.41.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.7->yolox==0.3.0) (3.25.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.7->yolox==0.3.0) (16.0.6)\n",
            "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (1.4.0)\n",
            "Requirement already satisfied: grpcio>=1.48.2 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (1.56.2)\n",
            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (2.17.3)\n",
            "Requirement already satisfied: google-auth-oauthlib<1.1,>=0.5 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (1.0.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (3.4.4)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (2.27.1)\n",
            "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (0.7.1)\n",
            "Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard->yolox==0.3.0) (2.3.6)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision->yolox==0.3.0) (9.4.0)\n",
            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->yolox==0.3.0) (5.3.1)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->yolox==0.3.0) (0.3.0)\n",
            "Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->yolox==0.3.0) (1.16.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard->yolox==0.3.0) (4.9)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<1.1,>=0.5->tensorboard->yolox==0.3.0) (1.3.1)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->yolox==0.3.0) (1.1.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->yolox==0.3.0) (0.11.0)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->yolox==0.3.0) (4.41.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->yolox==0.3.0) (1.4.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->yolox==0.3.0) (23.1)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->yolox==0.3.0) (3.1.0)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools>=2.0.2->yolox==0.3.0) (2.8.2)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard->yolox==0.3.0) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard->yolox==0.3.0) (2023.7.22)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard->yolox==0.3.0) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard->yolox==0.3.0) (3.4)\n",
            "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard->yolox==0.3.0) (2.1.3)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->onnx-simplifier==0.4.10->yolox==0.3.0) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->onnx-simplifier==0.4.10->yolox==0.3.0) (2.14.0)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.7->yolox==0.3.0) (1.3.0)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->onnx-simplifier==0.4.10->yolox==0.3.0) (0.1.2)\n",
            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard->yolox==0.3.0) (0.5.0)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<1.1,>=0.5->tensorboard->yolox==0.3.0) (3.2.2)\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mInstalling collected packages: yolox\n",
            "  Running setup.py develop for yolox\n",
            "    Running command python setup.py develop\n",
            "    /usr/local/lib/python3.10/dist-packages/setuptools/__init__.py:84: _DeprecatedInstaller: setuptools.installer and fetch_build_eggs are deprecated.\n",
            "    !!\n",
            "\n",
            "            ********************************************************************************\n",
            "            Requirements should be satisfied by a PEP 517 installer.\n",
            "            If you are using pip, you can try `pip install --use-pep517`.\n",
            "            ********************************************************************************\n",
            "\n",
            "    !!\n",
            "      dist.fetch_build_eggs(dist.setup_requires)\n",
            "    running develop\n",
            "    /usr/local/lib/python3.10/dist-packages/setuptools/command/develop.py:40: EasyInstallDeprecationWarning: easy_install command is deprecated.\n",
            "    !!\n",
            "\n",
            "            ********************************************************************************\n",
            "            Please avoid running ``setup.py`` and ``easy_install``.\n",
            "            Instead, use pypa/build, pypa/installer, pypa/build or\n",
            "            other standards-based tools.\n",
            "\n",
            "            See https://github.com/pypa/setuptools/issues/917 for details.\n",
            "            ********************************************************************************\n",
            "\n",
            "    !!\n",
            "      easy_install.initialize_options(self)\n",
            "    /usr/local/lib/python3.10/dist-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.\n",
            "    !!\n",
            "\n",
            "            ********************************************************************************\n",
            "            Please avoid running ``setup.py`` directly.\n",
            "            Instead, use pypa/build, pypa/installer, pypa/build or\n",
            "            other standards-based tools.\n",
            "\n",
            "            See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.\n",
            "            ********************************************************************************\n",
            "\n",
            "    !!\n",
            "      self.initialize_options()\n",
            "    running egg_info\n",
            "    creating yolox.egg-info\n",
            "    writing yolox.egg-info/PKG-INFO\n",
            "    writing dependency_links to yolox.egg-info/dependency_links.txt\n",
            "    writing requirements to yolox.egg-info/requires.txt\n",
            "    writing top-level names to yolox.egg-info/top_level.txt\n",
            "    writing manifest file 'yolox.egg-info/SOURCES.txt'\n",
            "    reading manifest file 'yolox.egg-info/SOURCES.txt'\n",
            "    reading manifest template 'MANIFEST.in'\n",
            "    warning: no files found matching '*.cu' under directory 'yolox'\n",
            "    warning: no files found matching '*.cuh' under directory 'yolox'\n",
            "    warning: no files found matching '*.cc' under directory 'yolox'\n",
            "    writing manifest file 'yolox.egg-info/SOURCES.txt'\n",
            "    running build_ext\n",
            "    building 'yolox.layers.fast_cocoeval' extension\n",
            "    creating /content/tfs-data-centric/build\n",
            "    creating /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310\n",
            "    creating /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310/yolox\n",
            "    creating /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310/yolox/layers\n",
            "    creating /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310/yolox/layers/cocoeval\n",
            "    Emitting ninja build file /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310/build.ninja...\n",
            "    Compiling objects...\n",
            "    Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)\n",
            "    [1/1] c++ -MMD -MF /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310/yolox/layers/cocoeval/cocoeval.o.d -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -fPIC -Iyolox/layers/cocoeval -I/usr/local/lib/python3.10/dist-packages/torch/include -I/usr/local/lib/python3.10/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.10/dist-packages/torch/include/TH -I/usr/local/lib/python3.10/dist-packages/torch/include/THC -I/usr/include/python3.10 -c -c /content/tfs-data-centric/yolox/layers/cocoeval/cocoeval.cpp -o /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310/yolox/layers/cocoeval/cocoeval.o -O3 -std=c++14 -g -Wno-reorder -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE=\"_gcc\"' '-DPYBIND11_STDLIB=\"_libstdcpp\"' '-DPYBIND11_BUILD_ABI=\"_cxxabi1011\"' -DTORCH_EXTENSION_NAME=fast_cocoeval -D_GLIBCXX_USE_CXX11_ABI=0\n",
            "    creating build/lib.linux-x86_64-cpython-310\n",
            "    creating build/lib.linux-x86_64-cpython-310/yolox\n",
            "    creating build/lib.linux-x86_64-cpython-310/yolox/layers\n",
            "    x86_64-linux-gnu-g++ -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -g -fwrapv -O2 /content/tfs-data-centric/build/temp.linux-x86_64-cpython-310/yolox/layers/cocoeval/cocoeval.o -L/usr/local/lib/python3.10/dist-packages/torch/lib -L/usr/lib/x86_64-linux-gnu -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-310/yolox/layers/fast_cocoeval.cpython-310-x86_64-linux-gnu.so\n",
            "    copying build/lib.linux-x86_64-cpython-310/yolox/layers/fast_cocoeval.cpython-310-x86_64-linux-gnu.so -> yolox/layers\n",
            "    Creating /usr/local/lib/python3.10/dist-packages/yolox.egg-link (link to .)\n",
            "    Adding yolox 0.3.0 to easy-install.pth file\n",
            "\n",
            "    Installed /content/tfs-data-centric\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0m\u001b[33mWARNING: Ignoring invalid distribution -orch (/usr/local/lib/python3.10/dist-packages)\u001b[0m\u001b[33m\n",
            "\u001b[0mSuccessfully installed yolox-0.3.0\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "%cd /content/\n",
        "!git clone https://github.com/makerviet/tfs-data-centric\n",
        "%cd /content/tfs-data-centric\n",
        "!pip3 install -U pip && pip3 install -r requirements.txt\n",
        "!pip3 install -v -e .  # or  python3 setup.py develop"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y4_IQ4odoil_"
      },
      "source": [
        "## 2. Dataset preparation\n",
        "\n",
        "Download sample data. You can upload your data to Google Drive and use `gdown` to get your data here.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DWKf7CVQOcvr",
        "outputId": "e0715f00-3508-45e4-c33d-8ab679a0c33e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[1;30;43mKết quả truyền trực tuyến bị cắt bớt đến 5000 dòng cuối.\u001b[0m\n",
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          ]
        }
      ],
      "source": [
        "%cd /content/tfs-data-centric\n",
        "!bash tools/download_data.sh"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DLdPkSckouBw"
      },
      "source": [
        "## 3. Training\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G5d4Rg7bRUCV",
        "outputId": "698fe148-37aa-403f-a94f-a8503bc45049"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "2023-08-04 18:06:32.331363: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
            "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
            "2023-08-04 18:06:34.685731: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "\u001b[32m2023-08-04 18:06:37\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m130\u001b[0m - \u001b[1margs: Namespace(experiment_name='tfs_nano', name=None, dist_backend='nccl', dist_url=None, batch_size=8, devices=None, exp_file='exps/tfs_nano.py', resume=False, ckpt=None, start_epoch=None, num_machines=1, machine_rank=0, fp16=False, cache=None, occupy=False, logger='tensorboard', opts=[])\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:37\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m131\u001b[0m - \u001b[1mexp value:\n",
            "╒═══════════════════╤═══════════════════════════╕\n",
            "│ keys              │ values                    │\n",
            "╞═══════════════════╪═══════════════════════════╡\n",
            "│ seed              │ None                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ output_dir        │ './YOLOX_outputs'         │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ print_interval    │ 10                        │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ eval_interval     │ 1                         │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ dataset           │ None                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ num_classes       │ 6                         │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ depth             │ 0.33                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ width             │ 0.25                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ act               │ 'silu'                    │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ data_num_workers  │ 4                         │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ input_size        │ (416, 416)                │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ multiscale_range  │ 5                         │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ data_dir          │ None                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ train_ann         │ 'train.json'              │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ val_ann           │ 'val.json'                │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ test_ann          │ 'instances_test2017.json' │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ mosaic_prob       │ 1.0                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ mixup_prob        │ 1.0                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ hsv_prob          │ 1.0                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ flip_prob         │ 0.5                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ degrees           │ 10.0                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ translate         │ 0.1                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ mosaic_scale      │ (0.1, 2)                  │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ enable_mixup      │ False                     │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ mixup_scale       │ (0.5, 1.5)                │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ shear             │ 2.0                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ warmup_epochs     │ 5                         │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ max_epoch         │ 40                        │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ warmup_lr         │ 0                         │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ min_lr_ratio      │ 0.05                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ basic_lr_per_img  │ 0.00125                   │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ scheduler         │ 'yoloxwarmcos'            │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ no_aug_epochs     │ 10                        │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ ema               │ True                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ weight_decay      │ 0.0005                    │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ momentum          │ 0.9                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ save_history_ckpt │ True                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ exp_name          │ 'tfs_nano'                │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ test_size         │ (416, 416)                │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ test_conf         │ 0.01                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ nmsthre           │ 0.65                      │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ random_size       │ (14, 26)                  │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ mirror            │ 0.0                       │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ scale             │ (0.5, 1.5)                │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ mscale            │ (0.8, 1.6)                │\n",
            "├───────────────────┼───────────────────────────┤\n",
            "│ perspective       │ 0.0                       │\n",
            "╘═══════════════════╧═══════════════════════════╛\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:37\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m136\u001b[0m - \u001b[1mModel Summary: Params: 2.24M, Gflops: 2.93\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:40\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.data.datasets.coco\u001b[0m:\u001b[36m63\u001b[0m - \u001b[1mloading annotations into memory...\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:40\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.data.datasets.coco\u001b[0m:\u001b[36m63\u001b[0m - \u001b[1mDone (t=0.04s)\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:40\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mpycocotools.coco\u001b[0m:\u001b[36m86\u001b[0m - \u001b[1mcreating index...\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:40\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mpycocotools.coco\u001b[0m:\u001b[36m86\u001b[0m - \u001b[1mindex created!\u001b[0m\n",
            "/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:560: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
            "  warnings.warn(_create_warning_msg(\n",
            "\u001b[32m2023-08-04 18:06:41\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m155\u001b[0m - \u001b[1minit prefetcher, this might take one minute or less...\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.data.datasets.coco\u001b[0m:\u001b[36m63\u001b[0m - \u001b[1mloading annotations into memory...\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.data.datasets.coco\u001b[0m:\u001b[36m63\u001b[0m - \u001b[1mDone (t=0.01s)\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mpycocotools.coco\u001b[0m:\u001b[36m86\u001b[0m - \u001b[1mcreating index...\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mpycocotools.coco\u001b[0m:\u001b[36m86\u001b[0m - \u001b[1mindex created!\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m196\u001b[0m - \u001b[1mTraining start...\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m197\u001b[0m - \u001b[1m\n",
            "YOLOX(\n",
            "  (backbone): YOLOPAFPN(\n",
            "    (backbone): CSPDarknet(\n",
            "      (stem): Focus(\n",
            "        (conv): BaseConv(\n",
            "          (conv): Conv2d(12, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(16, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "      )\n",
            "      (dark2): Sequential(\n",
            "        (0): BaseConv(\n",
            "          (conv): Conv2d(16, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "        (1): CSPLayer(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(32, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(16, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(32, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(16, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv3): BaseConv(\n",
            "            (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (m): Sequential(\n",
            "            (0): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(16, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(16, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(16, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (dark3): Sequential(\n",
            "        (0): BaseConv(\n",
            "          (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "        (1): CSPLayer(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv3): BaseConv(\n",
            "            (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (m): Sequential(\n",
            "            (0): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "            (1): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "            (2): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (dark4): Sequential(\n",
            "        (0): BaseConv(\n",
            "          (conv): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "        (1): CSPLayer(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv3): BaseConv(\n",
            "            (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (m): Sequential(\n",
            "            (0): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "            (1): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "            (2): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (dark5): Sequential(\n",
            "        (0): BaseConv(\n",
            "          (conv): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(256, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "        (1): SPPBottleneck(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (m): ModuleList(\n",
            "            (0): MaxPool2d(kernel_size=5, stride=1, padding=2, dilation=1, ceil_mode=False)\n",
            "            (1): MaxPool2d(kernel_size=9, stride=1, padding=4, dilation=1, ceil_mode=False)\n",
            "            (2): MaxPool2d(kernel_size=13, stride=1, padding=6, dilation=1, ceil_mode=False)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(256, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "        )\n",
            "        (2): CSPLayer(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv3): BaseConv(\n",
            "            (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(256, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (m): Sequential(\n",
            "            (0): Bottleneck(\n",
            "              (conv1): BaseConv(\n",
            "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "              (conv2): BaseConv(\n",
            "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "                (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "                (act): SiLU(inplace=True)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (upsample): Upsample(scale_factor=2.0, mode='nearest')\n",
            "    (lateral_conv0): BaseConv(\n",
            "      (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "      (act): SiLU(inplace=True)\n",
            "    )\n",
            "    (C3_p4): CSPLayer(\n",
            "      (conv1): BaseConv(\n",
            "        (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv2): BaseConv(\n",
            "        (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv3): BaseConv(\n",
            "        (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (m): Sequential(\n",
            "        (0): Bottleneck(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (reduce_conv1): BaseConv(\n",
            "      (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "      (act): SiLU(inplace=True)\n",
            "    )\n",
            "    (C3_p3): CSPLayer(\n",
            "      (conv1): BaseConv(\n",
            "        (conv): Conv2d(128, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv2): BaseConv(\n",
            "        (conv): Conv2d(128, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv3): BaseConv(\n",
            "        (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (m): Sequential(\n",
            "        (0): Bottleneck(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(32, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (bu_conv2): BaseConv(\n",
            "      (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "      (act): SiLU(inplace=True)\n",
            "    )\n",
            "    (C3_n3): CSPLayer(\n",
            "      (conv1): BaseConv(\n",
            "        (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv2): BaseConv(\n",
            "        (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv3): BaseConv(\n",
            "        (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (m): Sequential(\n",
            "        (0): Bottleneck(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (bu_conv1): BaseConv(\n",
            "      (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "      (act): SiLU(inplace=True)\n",
            "    )\n",
            "    (C3_n4): CSPLayer(\n",
            "      (conv1): BaseConv(\n",
            "        (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv2): BaseConv(\n",
            "        (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (conv3): BaseConv(\n",
            "        (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(256, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (m): Sequential(\n",
            "        (0): Bottleneck(\n",
            "          (conv1): BaseConv(\n",
            "            (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "          (conv2): BaseConv(\n",
            "            (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "            (bn): BatchNorm2d(128, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "            (act): SiLU(inplace=True)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "  )\n",
            "  (head): YOLOXHead(\n",
            "    (cls_convs): ModuleList(\n",
            "      (0-2): 3 x Sequential(\n",
            "        (0): BaseConv(\n",
            "          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "        (1): BaseConv(\n",
            "          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (reg_convs): ModuleList(\n",
            "      (0-2): 3 x Sequential(\n",
            "        (0): BaseConv(\n",
            "          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "        (1): BaseConv(\n",
            "          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "          (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "          (act): SiLU(inplace=True)\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (cls_preds): ModuleList(\n",
            "      (0-2): 3 x Conv2d(64, 6, kernel_size=(1, 1), stride=(1, 1))\n",
            "    )\n",
            "    (reg_preds): ModuleList(\n",
            "      (0-2): 3 x Conv2d(64, 4, kernel_size=(1, 1), stride=(1, 1))\n",
            "    )\n",
            "    (obj_preds): ModuleList(\n",
            "      (0-2): 3 x Conv2d(64, 1, kernel_size=(1, 1), stride=(1, 1))\n",
            "    )\n",
            "    (stems): ModuleList(\n",
            "      (0): BaseConv(\n",
            "        (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (1): BaseConv(\n",
            "        (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "      (2): BaseConv(\n",
            "        (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "        (bn): BatchNorm2d(64, eps=0.001, momentum=0.03, affine=True, track_running_stats=True)\n",
            "        (act): SiLU(inplace=True)\n",
            "      )\n",
            "    )\n",
            "    (l1_loss): L1Loss()\n",
            "    (bcewithlog_loss): BCEWithLogitsLoss()\n",
            "    (iou_loss): IOUloss()\n",
            "  )\n",
            ")\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m208\u001b[0m - \u001b[1m---> start train epoch1\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:53\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 10/1000, gpu mem: 1006Mb, mem: 3.2Gb, iter_time: 1.058s, data_time: 0.006s, total_loss: 24.7, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 19.2, cls_loss: 0.9, lr: 4.000e-08, size: 416, ETA: 11:44:56\u001b[0m\n",
            "\u001b[32m2023-08-04 18:06:57\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 20/1000, gpu mem: 3083Mb, mem: 3.2Gb, iter_time: 0.471s, data_time: 0.003s, total_loss: 70.6, iou_loss: 4.7, l1_loss: 0.0, conf_loss: 65.0, cls_loss: 0.9, lr: 1.600e-07, size: 832, ETA: 8:29:09\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:00\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 30/1000, gpu mem: 3083Mb, mem: 3.2Gb, iter_time: 0.200s, data_time: 0.002s, total_loss: 49.7, iou_loss: 4.7, l1_loss: 0.0, conf_loss: 44.2, cls_loss: 0.7, lr: 3.600e-07, size: 832, ETA: 6:23:47\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:03\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 40/1000, gpu mem: 3083Mb, mem: 3.2Gb, iter_time: 0.342s, data_time: 0.007s, total_loss: 27.8, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 22.2, cls_loss: 0.8, lr: 6.400e-07, size: 480, ETA: 5:44:43\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:07\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 50/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.401s, data_time: 0.006s, total_loss: 27.7, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 22.2, cls_loss: 0.7, lr: 1.000e-06, size: 544, ETA: 5:29:08\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:09\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 60/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.246s, data_time: 0.008s, total_loss: 24.7, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 19.1, cls_loss: 0.9, lr: 1.440e-06, size: 448, ETA: 5:01:28\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:11\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 70/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.139s, data_time: 0.008s, total_loss: 34.9, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 29.5, cls_loss: 0.6, lr: 1.960e-06, size: 544, ETA: 4:31:35\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:15\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 80/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.381s, data_time: 0.006s, total_loss: 47.2, iou_loss: 5.0, l1_loss: 0.0, conf_loss: 42.1, cls_loss: 0.2, lr: 2.560e-06, size: 672, ETA: 4:29:15\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:19\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 90/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.459s, data_time: 0.007s, total_loss: 32.0, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 26.4, cls_loss: 0.9, lr: 3.240e-06, size: 608, ETA: 4:33:11\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:22\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 100/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.233s, data_time: 0.007s, total_loss: 38.1, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 32.3, cls_loss: 1.3, lr: 4.000e-06, size: 544, ETA: 4:21:18\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:24\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 110/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.187s, data_time: 0.006s, total_loss: 28.6, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 22.9, cls_loss: 1.3, lr: 4.840e-06, size: 480, ETA: 4:08:46\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:28\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 120/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.476s, data_time: 0.002s, total_loss: 56.1, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 50.4, cls_loss: 1.0, lr: 5.760e-06, size: 800, ETA: 4:14:22\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:30\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 130/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.152s, data_time: 0.005s, total_loss: 34.7, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 29.3, cls_loss: 0.6, lr: 6.760e-06, size: 608, ETA: 4:02:29\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:35\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 140/1000, gpu mem: 3083Mb, mem: 3.4Gb, iter_time: 0.490s, data_time: 0.008s, total_loss: 48.7, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 42.8, cls_loss: 1.4, lr: 7.840e-06, size: 736, ETA: 4:08:21\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:37\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 150/1000, gpu mem: 3083Mb, mem: 3.3Gb, iter_time: 0.247s, data_time: 0.010s, total_loss: 26.8, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 21.1, cls_loss: 1.3, lr: 9.000e-06, size: 480, ETA: 4:02:41\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 160/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.494s, data_time: 0.002s, total_loss: 51.0, iou_loss: 4.7, l1_loss: 0.0, conf_loss: 45.5, cls_loss: 0.8, lr: 1.024e-05, size: 768, ETA: 4:07:59\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:44\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 170/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.192s, data_time: 0.002s, total_loss: 44.8, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 38.9, cls_loss: 1.6, lr: 1.156e-05, size: 800, ETA: 4:00:51\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:46\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 180/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 22.5, iou_loss: 4.7, l1_loss: 0.0, conf_loss: 16.9, cls_loss: 0.9, lr: 1.296e-05, size: 480, ETA: 3:52:34\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:47\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 190/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.150s, data_time: 0.010s, total_loss: 34.1, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 28.5, cls_loss: 1.1, lr: 1.444e-05, size: 608, ETA: 3:45:31\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:52\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 200/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.505s, data_time: 0.011s, total_loss: 23.7, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 18.0, cls_loss: 1.4, lr: 1.600e-05, size: 576, ETA: 3:50:56\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:55\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 210/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.258s, data_time: 0.010s, total_loss: 34.0, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 28.3, cls_loss: 1.1, lr: 1.764e-05, size: 608, ETA: 3:48:02\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:56\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 220/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.155s, data_time: 0.004s, total_loss: 25.3, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 19.7, cls_loss: 1.0, lr: 1.936e-05, size: 544, ETA: 3:42:17\u001b[0m\n",
            "\u001b[32m2023-08-04 18:07:58\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 230/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.187s, data_time: 0.004s, total_loss: 45.1, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 39.7, cls_loss: 0.7, lr: 2.116e-05, size: 736, ETA: 3:37:57\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:00\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 240/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.154s, data_time: 0.007s, total_loss: 20.0, iou_loss: 4.7, l1_loss: 0.0, conf_loss: 14.5, cls_loss: 0.8, lr: 2.304e-05, size: 448, ETA: 3:33:04\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:01\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 250/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.151s, data_time: 0.003s, total_loss: 22.7, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 17.1, cls_loss: 1.1, lr: 2.500e-05, size: 576, ETA: 3:28:29\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:03\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 260/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.201s, data_time: 0.003s, total_loss: 46.7, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 41.0, cls_loss: 1.2, lr: 2.704e-05, size: 800, ETA: 3:25:32\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:05\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 270/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.142s, data_time: 0.006s, total_loss: 22.4, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 16.8, cls_loss: 1.0, lr: 2.916e-05, size: 576, ETA: 3:21:21\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:07\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 280/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.250s, data_time: 0.005s, total_loss: 39.7, iou_loss: 4.9, l1_loss: 0.0, conf_loss: 34.3, cls_loss: 0.5, lr: 3.136e-05, size: 800, ETA: 3:20:01\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:10\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 290/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.247s, data_time: 0.006s, total_loss: 18.1, iou_loss: 4.7, l1_loss: 0.0, conf_loss: 12.6, cls_loss: 0.8, lr: 3.364e-05, size: 448, ETA: 3:18:43\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:12\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 300/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.222s, data_time: 0.009s, total_loss: 26.7, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 21.0, cls_loss: 1.2, lr: 3.600e-05, size: 608, ETA: 3:16:57\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:16\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 310/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.416s, data_time: 0.003s, total_loss: 33.2, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 27.5, cls_loss: 1.1, lr: 3.844e-05, size: 704, ETA: 3:19:25\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:20\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 320/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.377s, data_time: 0.006s, total_loss: 23.2, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 17.4, cls_loss: 1.2, lr: 4.096e-05, size: 640, ETA: 3:20:55\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:21\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 330/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 16.2, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 10.4, cls_loss: 1.5, lr: 4.356e-05, size: 448, ETA: 3:17:31\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:25\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 340/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.422s, data_time: 0.006s, total_loss: 17.2, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 11.4, cls_loss: 1.3, lr: 4.624e-05, size: 512, ETA: 3:19:52\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:28\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 350/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.250s, data_time: 0.006s, total_loss: 21.4, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 15.6, cls_loss: 1.6, lr: 4.900e-05, size: 672, ETA: 3:18:49\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:30\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 360/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.208s, data_time: 0.003s, total_loss: 31.4, iou_loss: 4.7, l1_loss: 0.0, conf_loss: 25.9, cls_loss: 0.9, lr: 5.184e-05, size: 800, ETA: 3:17:04\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:32\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 370/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.196s, data_time: 0.003s, total_loss: 21.4, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 15.7, cls_loss: 1.3, lr: 5.476e-05, size: 768, ETA: 3:15:11\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:34\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 380/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.208s, data_time: 0.002s, total_loss: 22.5, iou_loss: 4.8, l1_loss: 0.0, conf_loss: 17.1, cls_loss: 0.6, lr: 5.776e-05, size: 800, ETA: 3:13:37\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:36\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 390/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.147s, data_time: 0.004s, total_loss: 14.5, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 8.8, cls_loss: 1.3, lr: 6.084e-05, size: 512, ETA: 3:11:06\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:37\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 400/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.143s, data_time: 0.006s, total_loss: 13.8, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 7.8, cls_loss: 1.7, lr: 6.400e-05, size: 448, ETA: 3:08:38\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:39\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 410/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.216s, data_time: 0.005s, total_loss: 20.8, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 15.2, cls_loss: 1.2, lr: 6.724e-05, size: 736, ETA: 3:07:27\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:42\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 420/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.258s, data_time: 0.007s, total_loss: 18.8, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 13.2, cls_loss: 1.0, lr: 7.056e-05, size: 704, ETA: 3:07:00\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:44\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 430/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.250s, data_time: 0.008s, total_loss: 17.7, iou_loss: 4.4, l1_loss: 0.0, conf_loss: 12.0, cls_loss: 1.3, lr: 7.396e-05, size: 768, ETA: 3:06:26\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:46\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 440/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.143s, data_time: 0.006s, total_loss: 14.3, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 8.5, cls_loss: 1.2, lr: 7.744e-05, size: 544, ETA: 3:04:17\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:47\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 450/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.162s, data_time: 0.008s, total_loss: 16.3, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 10.6, cls_loss: 1.2, lr: 8.100e-05, size: 640, ETA: 3:02:31\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:49\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 460/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.153s, data_time: 0.005s, total_loss: 15.0, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 9.2, cls_loss: 1.5, lr: 8.464e-05, size: 608, ETA: 3:00:42\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:50\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 470/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.140s, data_time: 0.007s, total_loss: 14.1, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 8.4, cls_loss: 1.2, lr: 8.836e-05, size: 480, ETA: 2:58:46\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:52\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 480/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.142s, data_time: 0.008s, total_loss: 13.7, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 7.9, cls_loss: 1.3, lr: 9.216e-05, size: 480, ETA: 2:56:57\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:53\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 490/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.159s, data_time: 0.004s, total_loss: 15.9, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 10.4, cls_loss: 0.9, lr: 9.604e-05, size: 672, ETA: 2:55:26\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:56\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 500/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.228s, data_time: 0.003s, total_loss: 17.2, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 11.5, cls_loss: 1.5, lr: 1.000e-04, size: 768, ETA: 2:54:53\u001b[0m\n",
            "\u001b[32m2023-08-04 18:08:58\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 510/1000, gpu mem: 3083Mb, mem: 3.6Gb, iter_time: 0.232s, data_time: 0.009s, total_loss: 14.0, iou_loss: 4.0, l1_loss: 0.0, conf_loss: 8.2, cls_loss: 1.8, lr: 1.040e-04, size: 544, ETA: 2:54:24\u001b[0m\n",
            "\u001b[32m2023-08-04 18:09:01\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36myolox.core.trainer\u001b[0m:\u001b[36m260\u001b[0m - \u001b[1mepoch: 1/40, iter: 520/1000, gpu mem: 3083Mb, mem: 3.5Gb, iter_time: 0.254s, data_time: 0.007s, total_loss: 16.7, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 11.3, cls_loss: 0.9, lr: 1.082e-04, size: 736, ETA: 2:54:13\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "!YOLOX_DATADIR=datasets/vtfs/ python3 tools/train.py"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xku98mv5pzZT"
      },
      "source": [
        "## 4. Evaluation on validation set"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GEECla4dGJ23"
      },
      "outputs": [],
      "source": [
        "!YOLOX_WEIGHTS=YOLOX_outputs/tfs_nano/best_ckpt.pth YOLOX_DATADIR=datasets/vtfs python3 tools/eval.py --output_result=\"result.json\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z2tJkgPGu__A"
      },
      "source": [
        "## 5. Create a submission"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zQEpHOhRvC0T"
      },
      "outputs": [],
      "source": [
        "!python tools/create_submission.py --exp_dir=\"YOLOX_outputs/tfs_nano\" --output=\"submissions/submission_01.zip\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SWtrIYPCvGSh"
      },
      "source": [
        "Check the result at: `/content/tfs-data-centric/submissions/submission_01.zip`"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}