Hanqer_Deep_Hough_Transform_Train_SEL.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Hanqer_Deep_Hough_Transform_Train_SEL.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPp9FLJv4BHL1ShOrt2npr+",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/HassanBinHaroon/deep-hough-transform/blob/main/Hanqer_Deep_Hough_Transform_Train_SEL.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nqgnokXYmcbg",
        "outputId": "dbf93dcf-c688-45c3-bff5-0659d4ff418c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "fatal: destination path 'deep-hough-transform' already exists and is not an empty directory.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/Hanqer/deep-hough-transform.git"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd deep-hough-transform/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_1KiEG1pmnhA",
        "outputId": "6517fd5e-fefa-46df-9b03-a7d73b1ea75c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/deep-hough-transform\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget https://mcl.korea.ac.kr/research/Submitted/jtlee_slnet/ICCV2017_JTLEE_dataset.7z"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IiJGvRjCmpg5",
        "outputId": "35a1db3e-5c68-4172-8beb-524c85e71f3b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-08-10 23:25:31--  https://mcl.korea.ac.kr/research/Submitted/jtlee_slnet/ICCV2017_JTLEE_dataset.7z\n",
            "Resolving mcl.korea.ac.kr (mcl.korea.ac.kr)... 163.152.175.73\n",
            "Connecting to mcl.korea.ac.kr (mcl.korea.ac.kr)|163.152.175.73|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 183635100 (175M) [application/x-7z-compressed]\n",
            "Saving to: ‘ICCV2017_JTLEE_dataset.7z’\n",
            "\n",
            "ICCV2017_JTLEE_data 100%[===================>] 175.13M  12.2MB/s    in 16s     \n",
            "\n",
            "2022-08-10 23:25:49 (10.9 MB/s) - ‘ICCV2017_JTLEE_dataset.7z’ saved [183635100/183635100]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!7z x ICCV2017_JTLEE_dataset.7z "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_vuvYSZdmxVH",
        "outputId": "4b392423-ab95-415f-f9e5-8c88ddc68063"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "7-Zip [64] 16.02 : Copyright (c) 1999-2016 Igor Pavlov : 2016-05-21\n",
            "p7zip Version 16.02 (locale=en_US.UTF-8,Utf16=on,HugeFiles=on,64 bits,2 CPUs Intel(R) Xeon(R) CPU @ 2.30GHz (306F0),ASM,AES-NI)\n",
            "\n",
            "Scanning the drive for archives:\n",
            "  0M Scan\b\b\b\b\b\b\b\b\b         \b\b\b\b\b\b\b\b\b1 file, 183635100 bytes (176 MiB)\n",
            "\n",
            "Extracting archive: ICCV2017_JTLEE_dataset.7z\n",
            "--\n",
            "Path = ICCV2017_JTLEE_dataset.7z\n",
            "Type = 7z\n",
            "Physical Size = 183635100\n",
            "Headers Size = 30835\n",
            "Method = LZMA2:25\n",
            "Solid = +\n",
            "Blocks = 1\n",
            "\n",
            "  0%\b\b\b\b    \b\b\b\b  3% 36 - ICCV2017_JTLEE_images/0037.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                        \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b  8% 114 - ICCV2017_JTLEE_images/0115.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 14% 196 - ICCV2017_JTLEE_images/0197.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 17% 226 - ICCV2017_JTLEE_images/0227.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 19% 321 - ICCV2017_JTLEE_images/0322.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 21% 426 - ICCV2017_JTLEE_images/0427.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 24% 467 - ICCV2017_JTLEE_images/0468.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 27% 541 - ICCV2017_JTLEE_images/0542.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 30% 582 - ICCV2017_JTLEE_images/0583.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 32% 629 - ICCV2017_JTLEE_images/0630.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 35% 671 - ICCV2017_JTLEE_images/0672.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 38% 791 - ICCV2017_JTLEE_images/0792.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 42% 869 - ICCV2017_JTLEE_images/0870.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                         \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 45% 1000 - ICCV2017_JTLEE_images/1001.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 49% 1065 - ICCV2017_JTLEE_images/1066.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 53% 1169 - ICCV2017_JTLEE_images/1170.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 56% 1300 - ICCV2017_JTLEE_images/1301.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 60% 1390 - ICCV2017_JTLEE_images/1391.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 63% 1513 - ICCV2017_JTLEE_images/1514.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 67% 1590 - ICCV2017_JTLEE_images/1591.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 73% 1629 - ICCV2017_JTLEE_images/1630.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 76% 1676 - ICCV2017_JTLEE_images/1677.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 80% 1685 - ICCV2017_JTLEE_images/1686.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 84% 1698 - ICCV2017_JTLEE_images/1699.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 86% 1701 - ICCV2017_JTLEE_images/1702.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 89% 1704 - ICCV2017_JTLEE_images/1705.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 91% 1707 - ICCV2017_JTLEE_images/1708.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 97% 1712 - ICCV2017_JTLEE_images/1713.jpg\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                          \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 99% 1950 - ICCV2017_JTLEE_gtlines_all/0235.txt\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                               \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 99% 2868 - ICCV2017_JTLEE_gtlines_all/1153.txt\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                               \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 99% 3372 - ICCV2017_JTLEE_gtlines_all/1657.txt\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                               \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\bEverything is Ok\n",
            "\n",
            "Folders: 3\n",
            "Files: 3610\n",
            "Size:       186747814\n",
            "Compressed: 183635100\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd model/_cdht"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2JCPB5vwm2Zo",
        "outputId": "9e4f51be-7f33-4d00-e73b-d1a28aa846cd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/deep-hough-transform/model/_cdht\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python setup.py build"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "meYMwJf3m50H",
        "outputId": "74655b4c-598f-4f0d-f053-3e08edb8edb1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "running build\n",
            "running build_ext\n",
            "/usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:411: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.\n",
            "  warnings.warn(msg.format('we could not find ninja.'))\n",
            "/usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:813: UserWarning: The detected CUDA version (11.1) has a minor version mismatch with the version that was used to compile PyTorch (11.3). Most likely this shouldn't be a problem.\n",
            "  warnings.warn(CUDA_MISMATCH_WARN.format(cuda_str_version, torch.version.cuda))\n",
            "building 'deep_hough' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c deep_hough_cuda.cpp -o build/temp.linux-x86_64-3.7/deep_hough_cuda.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1013\" -DTORCH_EXTENSION_NAME=deep_hough -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Device.h:5:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Allocator.h:6\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:7\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kstd::vector<at::Tensor> line_accum_forward(at::Tensor, at::Tensor, int, int)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:40:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kat::DeprecatedTypeProperties& at::Tensor::type() const\u001b[m\u001b[K’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            " #define CHECK_CUDA(x) AT_ASSERT(x.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K.is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                                        \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:260:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin definition of macro ‘\u001b[01m\u001b[KC10_EXPAND_MSVC_WORKAROUND\u001b[m\u001b[K’\n",
            " #define C10_EXPAND_MSVC_WORKAROUND(x) \u001b[01;36m\u001b[Kx\u001b[m\u001b[K\n",
            "                                       \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:280:34:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY\u001b[m\u001b[K’\n",
            " #define C10_UNLIKELY_OR_CONST(e) \u001b[01;36m\u001b[KC10_UNLIKELY\u001b[m\u001b[K(e)\n",
            "                                  \u001b[01;36m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:332:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K’\n",
            "   if (\u001b[01;36m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K(!(cond))) {                                          \\\n",
            "       \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:613:32:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K’\n",
            "     C10_EXPAND_MSVC_WORKAROUND(\u001b[01;36m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K(__VA_ARGS__)); \\\n",
            "                                \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:23:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KAT_ASSERT\u001b[m\u001b[K’\n",
            " #define CHECK_CUDA(x) \u001b[01;36m\u001b[KAT_ASSERT\u001b[m\u001b[K(x.type().is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                       \u001b[01;36m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:30:24:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_CUDA\u001b[m\u001b[K’\n",
            " #define CHECK_INPUT(x) \u001b[01;36m\u001b[KCHECK_CUDA\u001b[m\u001b[K(x); CHECK_CONTIGUOUS(x)\n",
            "                        \u001b[01;36m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:52:5:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_INPUT\u001b[m\u001b[K’\n",
            "     \u001b[01;36m\u001b[KC\u001b[m\u001b[KHECK_INPUT(feat);\n",
            "     \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/DeviceGuard.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:11\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:213:30:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   DeprecatedTypeProperties & \u001b[01;36m\u001b[Ktype\u001b[m\u001b[K() const {\n",
            "                              \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Device.h:5:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Allocator.h:6\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:7\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:40:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kat::DeprecatedTypeProperties& at::Tensor::type() const\u001b[m\u001b[K’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            " #define CHECK_CUDA(x) AT_ASSERT(x.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K.is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                                        \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:260:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin definition of macro ‘\u001b[01m\u001b[KC10_EXPAND_MSVC_WORKAROUND\u001b[m\u001b[K’\n",
            " #define C10_EXPAND_MSVC_WORKAROUND(x) \u001b[01;36m\u001b[Kx\u001b[m\u001b[K\n",
            "                                       \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:280:34:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY\u001b[m\u001b[K’\n",
            " #define C10_UNLIKELY_OR_CONST(e) \u001b[01;36m\u001b[KC10_UNLIKELY\u001b[m\u001b[K(e)\n",
            "                                  \u001b[01;36m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:332:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K’\n",
            "   if (\u001b[01;36m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K(!(cond))) {                                          \\\n",
            "       \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:613:32:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K’\n",
            "     C10_EXPAND_MSVC_WORKAROUND(\u001b[01;36m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K(__VA_ARGS__)); \\\n",
            "                                \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:23:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KAT_ASSERT\u001b[m\u001b[K’\n",
            " #define CHECK_CUDA(x) \u001b[01;36m\u001b[KAT_ASSERT\u001b[m\u001b[K(x.type().is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                       \u001b[01;36m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:30:24:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_CUDA\u001b[m\u001b[K’\n",
            " #define CHECK_INPUT(x) \u001b[01;36m\u001b[KCHECK_CUDA\u001b[m\u001b[K(x); CHECK_CONTIGUOUS(x)\n",
            "                        \u001b[01;36m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:53:5:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_INPUT\u001b[m\u001b[K’\n",
            "     \u001b[01;36m\u001b[KC\u001b[m\u001b[KHECK_INPUT(output);\n",
            "     \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/DeviceGuard.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:11\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:213:30:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   DeprecatedTypeProperties & \u001b[01;36m\u001b[Ktype\u001b[m\u001b[K() const {\n",
            "                              \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:58:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kbatch_size\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[Kbatch_size\u001b[m\u001b[K = feat.size(0);\n",
            "               \u001b[01;35m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:59:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kchannels_size\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[Kchannels_size\u001b[m\u001b[K = feat.size(1);\n",
            "               \u001b[01;35m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Device.h:5:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Allocator.h:6\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:7\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kstd::vector<at::Tensor> line_accum_backward(at::Tensor, at::Tensor, at::Tensor, int, int)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:40:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kat::DeprecatedTypeProperties& at::Tensor::type() const\u001b[m\u001b[K’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            " #define CHECK_CUDA(x) AT_ASSERT(x.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K.is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                                        \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:260:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin definition of macro ‘\u001b[01m\u001b[KC10_EXPAND_MSVC_WORKAROUND\u001b[m\u001b[K’\n",
            " #define C10_EXPAND_MSVC_WORKAROUND(x) \u001b[01;36m\u001b[Kx\u001b[m\u001b[K\n",
            "                                       \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:280:34:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY\u001b[m\u001b[K’\n",
            " #define C10_UNLIKELY_OR_CONST(e) \u001b[01;36m\u001b[KC10_UNLIKELY\u001b[m\u001b[K(e)\n",
            "                                  \u001b[01;36m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:332:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K’\n",
            "   if (\u001b[01;36m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K(!(cond))) {                                          \\\n",
            "       \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:613:32:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K’\n",
            "     C10_EXPAND_MSVC_WORKAROUND(\u001b[01;36m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K(__VA_ARGS__)); \\\n",
            "                                \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:23:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KAT_ASSERT\u001b[m\u001b[K’\n",
            " #define CHECK_CUDA(x) \u001b[01;36m\u001b[KAT_ASSERT\u001b[m\u001b[K(x.type().is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                       \u001b[01;36m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:30:24:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_CUDA\u001b[m\u001b[K’\n",
            " #define CHECK_INPUT(x) \u001b[01;36m\u001b[KCHECK_CUDA\u001b[m\u001b[K(x); CHECK_CONTIGUOUS(x)\n",
            "                        \u001b[01;36m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:75:5:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_INPUT\u001b[m\u001b[K’\n",
            "     \u001b[01;36m\u001b[KC\u001b[m\u001b[KHECK_INPUT(grad_outputs);\n",
            "     \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/DeviceGuard.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:11\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:213:30:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   DeprecatedTypeProperties & \u001b[01;36m\u001b[Ktype\u001b[m\u001b[K() const {\n",
            "                              \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Device.h:5:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Allocator.h:6\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:7\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:40:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kat::DeprecatedTypeProperties& at::Tensor::type() const\u001b[m\u001b[K’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            " #define CHECK_CUDA(x) AT_ASSERT(x.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K.is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                                        \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:260:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin definition of macro ‘\u001b[01m\u001b[KC10_EXPAND_MSVC_WORKAROUND\u001b[m\u001b[K’\n",
            " #define C10_EXPAND_MSVC_WORKAROUND(x) \u001b[01;36m\u001b[Kx\u001b[m\u001b[K\n",
            "                                       \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:280:34:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY\u001b[m\u001b[K’\n",
            " #define C10_UNLIKELY_OR_CONST(e) \u001b[01;36m\u001b[KC10_UNLIKELY\u001b[m\u001b[K(e)\n",
            "                                  \u001b[01;36m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:332:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K’\n",
            "   if (\u001b[01;36m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K(!(cond))) {                                          \\\n",
            "       \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:613:32:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K’\n",
            "     C10_EXPAND_MSVC_WORKAROUND(\u001b[01;36m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K(__VA_ARGS__)); \\\n",
            "                                \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:23:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KAT_ASSERT\u001b[m\u001b[K’\n",
            " #define CHECK_CUDA(x) \u001b[01;36m\u001b[KAT_ASSERT\u001b[m\u001b[K(x.type().is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                       \u001b[01;36m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:30:24:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_CUDA\u001b[m\u001b[K’\n",
            " #define CHECK_INPUT(x) \u001b[01;36m\u001b[KCHECK_CUDA\u001b[m\u001b[K(x); CHECK_CONTIGUOUS(x)\n",
            "                        \u001b[01;36m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:76:5:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_INPUT\u001b[m\u001b[K’\n",
            "     \u001b[01;36m\u001b[KC\u001b[m\u001b[KHECK_INPUT(grad_inputs);\n",
            "     \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/DeviceGuard.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:11\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:213:30:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   DeprecatedTypeProperties & \u001b[01;36m\u001b[Ktype\u001b[m\u001b[K() const {\n",
            "                              \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Device.h:5:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/Allocator.h:6\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:7\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:40:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kat::DeprecatedTypeProperties& at::Tensor::type() const\u001b[m\u001b[K’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            " #define CHECK_CUDA(x) AT_ASSERT(x.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K.is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                                        \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:260:39:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin definition of macro ‘\u001b[01m\u001b[KC10_EXPAND_MSVC_WORKAROUND\u001b[m\u001b[K’\n",
            " #define C10_EXPAND_MSVC_WORKAROUND(x) \u001b[01;36m\u001b[Kx\u001b[m\u001b[K\n",
            "                                       \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:280:34:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY\u001b[m\u001b[K’\n",
            " #define C10_UNLIKELY_OR_CONST(e) \u001b[01;36m\u001b[KC10_UNLIKELY\u001b[m\u001b[K(e)\n",
            "                                  \u001b[01;36m\u001b[K^~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:332:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K’\n",
            "   if (\u001b[01;36m\u001b[KC10_UNLIKELY_OR_CONST\u001b[m\u001b[K(!(cond))) {                                          \\\n",
            "       \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/c10/util/Exception.h:613:32:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K’\n",
            "     C10_EXPAND_MSVC_WORKAROUND(\u001b[01;36m\u001b[KTORCH_INTERNAL_ASSERT\u001b[m\u001b[K(__VA_ARGS__)); \\\n",
            "                                \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:28:23:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KAT_ASSERT\u001b[m\u001b[K’\n",
            " #define CHECK_CUDA(x) \u001b[01;36m\u001b[KAT_ASSERT\u001b[m\u001b[K(x.type().is_cuda()) //, #x \" must be a CUDA tensor\")\n",
            "                       \u001b[01;36m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:30:24:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_CUDA\u001b[m\u001b[K’\n",
            " #define CHECK_INPUT(x) \u001b[01;36m\u001b[KCHECK_CUDA\u001b[m\u001b[K(x); CHECK_CONTIGUOUS(x)\n",
            "                        \u001b[01;36m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:77:5:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KCHECK_INPUT\u001b[m\u001b[K’\n",
            "     \u001b[01;36m\u001b[KC\u001b[m\u001b[KHECK_INPUT(feat);\n",
            "     \u001b[01;36m\u001b[K^\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/DeviceGuard.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:11\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:8\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Kdeep_hough_cuda.cpp:1\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:213:30:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   DeprecatedTypeProperties & \u001b[01;36m\u001b[Ktype\u001b[m\u001b[K() const {\n",
            "                              \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:84:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kbatch_size\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[Kbatch_size\u001b[m\u001b[K = feat.size(0);\n",
            "               \u001b[01;35m\u001b[K^~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:85:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[Kchannels_size\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[Kchannels_size\u001b[m\u001b[K = feat.size(1);\n",
            "               \u001b[01;35m\u001b[K^~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:86:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[KimH\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[KimH\u001b[m\u001b[K = feat.size(2);\n",
            "               \u001b[01;35m\u001b[K^~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda.cpp:87:15:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kunused variable ‘\u001b[01m\u001b[KimW\u001b[m\u001b[K’ [\u001b[01;35m\u001b[K-Wunused-variable\u001b[m\u001b[K]\n",
            "     const int \u001b[01;35m\u001b[KimW\u001b[m\u001b[K = feat.size(3);\n",
            "               \u001b[01;35m\u001b[K^~~\u001b[m\u001b[K\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c deep_hough_cuda_kernel.cu -o build/temp.linux-x86_64-3.7/deep_hough_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -arch=sm_60 -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1013\" -DTORCH_EXTENSION_NAME=deep_hough -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/SymInt.h(84): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "deep_hough_cuda_kernel.cu(19): warning: argument is incompatible with corresponding format string conversion\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/c10/core/SymInt.h(84): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda_kernel.cu:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kstd::vector<at::Tensor> line_accum_cuda_forward(at::Tensor, const float*, const float*, at::Tensor, int, int)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda_kernel.cu:215:105:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = float]\u001b[m\u001b[K’ is deprecated: Tensor.data<T>() is deprecated. Please use Tensor.data_ptr<T>() instead. [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     line_accum_forward_kernel<<<blocks, threads>>>(\n",
            "                                                                                                         \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:235:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[K  T \u001b[m\u001b[K* data() const {\n",
            " \u001b[01;36m\u001b[K^\u001b[m\u001b[K \u001b[01;36m\u001b[K~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda_kernel.cu:215:149:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = float]\u001b[m\u001b[K’ is deprecated: Tensor.data<T>() is deprecated. Please use Tensor.data_ptr<T>() instead. [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     line_accum_forward_kernel<<<blocks, threads>>>(\n",
            "                                                                                                                                                     \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:235:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[K  T \u001b[m\u001b[K* data() const {\n",
            " \u001b[01;36m\u001b[K^\u001b[m\u001b[K \u001b[01;36m\u001b[K~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda_kernel.cu:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kstd::vector<at::Tensor> line_accum_cuda_backward(at::Tensor, at::Tensor, at::Tensor, const float*, const float*, int, int)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda_kernel.cu:278:109:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = float]\u001b[m\u001b[K’ is deprecated: Tensor.data<T>() is deprecated. Please use Tensor.data_ptr<T>() instead. [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     line_accum_backward_kernel<<<blocks, threads>>>(\n",
            "                                                                                                             \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:235:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[K  T \u001b[m\u001b[K* data() const {\n",
            " \u001b[01;36m\u001b[K^\u001b[m\u001b[K \u001b[01;36m\u001b[K~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kdeep_hough_cuda_kernel.cu:278:139:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = float]\u001b[m\u001b[K’ is deprecated: Tensor.data<T>() is deprecated. Please use Tensor.data_ptr<T>() instead. [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     line_accum_backward_kernel<<<blocks, threads>>>(\n",
            "                                                                                                                                           \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:235:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[K  T \u001b[m\u001b[K* data() const {\n",
            " \u001b[01;36m\u001b[K^\u001b[m\u001b[K \u001b[01;36m\u001b[K~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -g -fwrapv -O2 -Wl,-Bsymbolic-functions -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/deep_hough_cuda.o build/temp.linux-x86_64-3.7/deep_hough_cuda_kernel.o -L/usr/local/lib/python3.7/dist-packages/torch/lib -L/usr/local/cuda/lib64 -lc10 -ltorch -ltorch_cpu -ltorch_python -lcudart -lc10_cuda -ltorch_cuda_cu -ltorch_cuda_cpp -o build/lib.linux-x86_64-3.7/deep_hough.cpython-37m-x86_64-linux-gnu.so\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python setup.py install --user"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "122I_HdBm7kQ",
        "outputId": "cfb6d308-b2cd-4edf-cdf2-56ef01b36d8b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "running install\n",
            "running bdist_egg\n",
            "running egg_info\n",
            "creating deep_hough.egg-info\n",
            "writing deep_hough.egg-info/PKG-INFO\n",
            "writing dependency_links to deep_hough.egg-info/dependency_links.txt\n",
            "writing top-level names to deep_hough.egg-info/top_level.txt\n",
            "writing manifest file 'deep_hough.egg-info/SOURCES.txt'\n",
            "/usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:411: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.\n",
            "  warnings.warn(msg.format('we could not find ninja.'))\n",
            "writing manifest file 'deep_hough.egg-info/SOURCES.txt'\n",
            "installing library code to build/bdist.linux-x86_64/egg\n",
            "running install_lib\n",
            "running build_ext\n",
            "/usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:813: UserWarning: The detected CUDA version (11.1) has a minor version mismatch with the version that was used to compile PyTorch (11.3). Most likely this shouldn't be a problem.\n",
            "  warnings.warn(CUDA_MISMATCH_WARN.format(cuda_str_version, torch.version.cuda))\n",
            "creating build/bdist.linux-x86_64\n",
            "creating build/bdist.linux-x86_64/egg\n",
            "copying build/lib.linux-x86_64-3.7/deep_hough.cpython-37m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n",
            "creating stub loader for deep_hough.cpython-37m-x86_64-linux-gnu.so\n",
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            "copying deep_hough.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
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            "Extracting deep_hough-0.0.0-py3.7-linux-x86_64.egg to /root/.local/lib/python3.7/site-packages\n",
            "Adding deep-hough 0.0.0 to easy-install.pth file\n",
            "\n",
            "Installed /root/.local/lib/python3.7/site-packages/deep_hough-0.0.0-py3.7-linux-x86_64.egg\n",
            "Processing dependencies for deep-hough==0.0.0\n",
            "Finished processing dependencies for deep-hough==0.0.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd ../.."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cg-Abq05m91n",
        "outputId": "70903911-6a17-4252-dbc6-7b0353b56f09"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/deep-hough-transform\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install tensorboardX"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LfuDHnl1nA3f",
        "outputId": "3b0bead9-4336-48f6-854e-e1abf7059a4a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting tensorboardX\n",
            "  Downloading tensorboardX-2.5.1-py2.py3-none-any.whl (125 kB)\n",
            "\u001b[K     |████████████████████████████████| 125 kB 4.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: protobuf<=3.20.1,>=3.8.0 in /usr/local/lib/python3.7/dist-packages (from tensorboardX) (3.17.3)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from tensorboardX) (1.21.6)\n",
            "Requirement already satisfied: six>=1.9 in /usr/local/lib/python3.7/dist-packages (from protobuf<=3.20.1,>=3.8.0->tensorboardX) (1.15.0)\n",
            "Installing collected packages: tensorboardX\n",
            "Successfully installed tensorboardX-2.5.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install POT"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eZ7IHdM1nCPn",
        "outputId": "d3f12b8b-cefe-429f-b2d6-f9685ac58633"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting POT\n",
            "  Downloading POT-0.8.2-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (664 kB)\n",
            "\u001b[K     |████████████████████████████████| 664 kB 4.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.7/dist-packages (from POT) (1.7.3)\n",
            "Requirement already satisfied: numpy>=1.16 in /usr/local/lib/python3.7/dist-packages (from POT) (1.21.6)\n",
            "Installing collected packages: POT\n",
            "Successfully installed POT-0.8.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install Ninja"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nGJv8uhqnEHP",
        "outputId": "f8c00405-198e-4487-cebf-858c6f9b57b3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting Ninja\n",
            "  Downloading ninja-1.10.2.3-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB)\n",
            "\u001b[K     |████████████████████████████████| 108 kB 4.8 MB/s \n",
            "\u001b[?25hInstalling collected packages: Ninja\n",
            "Successfully installed Ninja-1.10.2.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python data/prepare_data_JTLEE.py --root './ICCV2017_JTLEE_images/' --label './ICCV2017_JTLEE_gtlines_all' --save-dir './data/training/JTLEE_resize_100_100/' --list './data/training/JTLEE.lst' --prefix 'JTLEE_resize_100_100' --fixsize 400 --numangle 100 --numrho 100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wQdivilPnFeH",
        "outputId": "37acf769-7df1-46c8-c639-5b519cd63e56"
      },
      "execution_count": null,
      "outputs": [
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python train.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "peWdqn5pnNUg",
        "outputId": "6dade221-ed01-4ec1-a366-265e9bbf11e3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2022-08-10 23:29:03,759 INFO {'DATA': {'DIR': 'data/training/', 'VAL_DIR': 'data/training/', 'TEST_DIR': 'data/training', 'LABEL_FILE': 'data/training/train_1716_100_100.txt', 'VAL_LABEL_FILE': 'data/training/test_1716_100_100.txt', 'TEST_LABEL_FILE': 'data/training/test_1716_100_100.txt', 'BATCH_SIZE': 8, 'WORKERS': 4}, 'OPTIMIZER': {'LR': 0.0002, 'MOMENTUM': 0.9, 'GAMMA': 0.1, 'WEIGHT_DECAY': 0.0, 'STEPS': []}, 'MODEL': {'NUMANGLE': 100, 'NUMRHO': 100, 'FIX': True, 'THRESHOLD': 0.01, 'EDGE_ALIGN': False, 'BACKBONE': 'resnet50'}, 'TRAIN': {'EPOCHS': 30, 'PRINT_FREQ': 100, 'TEST': False, 'SEED': 1997, 'GPU_ID': 0, 'DATA_PARALLEL': False, 'RESUME': None}, 'MISC': {'TMP': './result/reproduce'}}\n",
            "2022-08-10 23:29:03,760 INFO Namespace(config='./config.yml', resume='', tmp='')\n",
            "Downloading: \"https://download.pytorch.org/models/resnet50-19c8e357.pth\" to /root/.cache/torch/hub/checkpoints/resnet50-19c8e357.pth\n",
            "100% 97.8M/97.8M [00:03<00:00, 33.2MB/s]\n",
            "/usr/local/lib/python3.7/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",
            "  cpuset_checked))\n",
            "2022-08-10 23:29:14,468 INFO Data loading done.\n",
            "2022-08-10 23:29:14,470 INFO Start training.\n",
            "  0% 0/386 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3722: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.\n",
            "  warnings.warn(\"nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.\")\n",
            "Training Loss:0.009840678423643112: 100% 386/386 [05:01<00:00,  1.28it/s]\n",
            "100% 174/174 [00:09<00:00, 17.83it/s]\n",
            "2022-08-10 23:34:26,214 INFO Validation result: ==== Precision: 0.36074, Recall: 0.69968\n",
            "2022-08-10 23:34:26,214 INFO Validation result: ==== F-measure: 0.47604\n",
            "2022-08-10 23:34:26,215 INFO Validation result: ==== F-measure@0.95: 0.09589\n",
            "2022-08-10 23:34:28,338 INFO Epoch 0/30 finishied, auxiliaries saved to ./result/reproduce .\tElapsed 0 days 0 hours 5 minutes.\tRemaining 0 days 2 hours 31 minutes.\n",
            "Training Loss:0.005776625592261553:  71% 275/386 [03:33<01:25,  1.30it/s]Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7f0b87544b00>\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py\", line 1481, in __del__\n",
            "    self._shutdown_workers()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py\", line 1426, in _shutdown_workers\n",
            "    self._worker_result_queue.put((None, None))\n",
            "  File \"/usr/lib/python3.7/multiprocessing/queues.py\", line 87, in put\n",
            "    self._start_thread()\n",
            "  File \"/usr/lib/python3.7/multiprocessing/queues.py\", line 170, in _start_thread\n",
            "    self._thread.start()\n",
            "  File \"/usr/lib/python3.7/threading.py\", line 857, in start\n",
            "    self._started.wait()\n",
            "  File \"/usr/lib/python3.7/threading.py\", line 552, in wait\n",
            "    signaled = self._cond.wait(timeout)\n",
            "  File \"/usr/lib/python3.7/threading.py\", line 296, in wait\n",
            "    waiter.acquire()\n",
            "KeyboardInterrupt: \n",
            "Training Loss:0.005776625592261553:  71% 275/386 [03:33<01:26,  1.29it/s]\n",
            "Traceback (most recent call last):\n",
            "  File \"train.py\", line 326, in <module>\n",
            "    main()\n",
            "  File \"train.py\", line 121, in main\n",
            "    train(train_loader, model, optimizer, epoch, writer, args)\n",
            "  File \"train.py\", line 190, in train\n",
            "    optimizer.step()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/optim/lr_scheduler.py\", line 65, in wrapper\n",
            "    return wrapped(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/optim/optimizer.py\", line 109, in wrapper\n",
            "    return func(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/autograd/grad_mode.py\", line 27, in decorate_context\n",
            "    return func(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/optim/adam.py\", line 171, in step\n",
            "    capturable=group['capturable'])\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/optim/adam.py\", line 226, in adam\n",
            "    capturable=capturable)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/optim/adam.py\", line 264, in _single_tensor_adam\n",
            "    exp_avg.mul_(beta1).add_(grad, alpha=1 - beta1)\n",
            "KeyboardInterrupt\n"
          ]
        }
      ]
    }
  ]
}