Hanqer_Deep_Hough_Transform_Train_NKL.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Hanqer_Deep_Hough_Transform_Train_NKL.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOgN9PYqOiUASt0eQ4q+q18",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard",
    "accelerator": "GPU"
  },
  "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_NKL.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ItmA6UjmzbhD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bdacef05-b4d6-4b3f-dda9-210815ed4ca5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'deep-hough-transform'...\n",
            "remote: Enumerating objects: 609, done.\u001b[K\n",
            "remote: Counting objects: 100% (30/30), done.\u001b[K\n",
            "remote: Compressing objects: 100% (20/20), done.\u001b[K\n",
            "remote: Total 609 (delta 16), reused 11 (delta 10), pack-reused 579\u001b[K\n",
            "Receiving objects: 100% (609/609), 13.86 MiB | 39.42 MiB/s, done.\n",
            "Resolving deltas: 100% (107/107), done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/Hanqer/deep-hough-transform.git"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd deep-hough-transform/"
      ],
      "metadata": {
        "id": "4DAWrmRNzsuP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d12bb730-21b7-4b14-82ac-cec0f0be3d01"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/deep-hough-transform\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget http://data.kaizhao.net/projects/deep-hough-transform/NKL.zip"
      ],
      "metadata": {
        "id": "FQMKER-_zypl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a32f6314-be88-4d57-c253-69dd72999bf5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-08-10 09:11:17--  http://data.kaizhao.net/projects/deep-hough-transform/NKL.zip\n",
            "Resolving data.kaizhao.net (data.kaizhao.net)... 104.21.43.242, 172.67.190.95, 2606:4700:3030::6815:2bf2, ...\n",
            "Connecting to data.kaizhao.net (data.kaizhao.net)|104.21.43.242|:80... connected.\n",
            "HTTP request sent, awaiting response... 301 Moved Permanently\n",
            "Location: https://data.kaizhao.net/projects/deep-hough-transform/NKL.zip [following]\n",
            "--2022-08-10 09:11:17--  https://data.kaizhao.net/projects/deep-hough-transform/NKL.zip\n",
            "Connecting to data.kaizhao.net (data.kaizhao.net)|104.21.43.242|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 581179759 (554M) [application/zip]\n",
            "Saving to: ‘NKL.zip’\n",
            "\n",
            "NKL.zip             100%[===================>] 554.26M  2.40MB/s    in 3m 57s  \n",
            "\n",
            "2022-08-10 09:15:18 (2.34 MB/s) - ‘NKL.zip’ saved [581179759/581179759]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip NKL.zip -d data/"
      ],
      "metadata": {
        "id": "j5qYBwkHag_l",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5016b586-d87c-4bc8-fa74-3a00b8aefb5a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "  inflating: data/NKL/999.jpg        \n",
            "  inflating: data/NKL/999.txt        \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd model/_cdht"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "15KyVP0ZQWGH",
        "outputId": "d3c1cba6-bca7-4775-e459-6b4134f7d864"
      },
      "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": "U45Rtw0RQZxe",
        "outputId": "8809a203-64e3-492b-dbeb-9625483250e4"
      },
      "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": "Ir4QuLOMQdvG",
        "outputId": "373649d0-db5c-42ec-ed1c-55b0653743f2"
      },
      "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",
            "byte-compiling build/bdist.linux-x86_64/egg/deep_hough.py to deep_hough.cpython-37.pyc\n",
            "creating build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying deep_hough.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying deep_hough.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying deep_hough.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying deep_hough.egg-info/top_level.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "writing build/bdist.linux-x86_64/egg/EGG-INFO/native_libs.txt\n",
            "zip_safe flag not set; analyzing archive contents...\n",
            "__pycache__.deep_hough.cpython-37: module references __file__\n",
            "creating dist\n",
            "creating 'dist/deep_hough-0.0.0-py3.7-linux-x86_64.egg' and adding 'build/bdist.linux-x86_64/egg' to it\n",
            "removing 'build/bdist.linux-x86_64/egg' (and everything under it)\n",
            "Processing deep_hough-0.0.0-py3.7-linux-x86_64.egg\n",
            "creating /root/.local/lib/python3.7/site-packages/deep_hough-0.0.0-py3.7-linux-x86_64.egg\n",
            "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": "pYWzFm7-RFjW",
        "outputId": "a9cf06db-35b1-4347-b2fa-7f5ba08eb3f6"
      },
      "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": "ifTHYUXpf3-M",
        "outputId": "392ac6b3-6813-4f91-bfd1-6e8712537505"
      },
      "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[?25l\r\u001b[K     |██▋                             | 10 kB 29.9 MB/s eta 0:00:01\r\u001b[K     |█████▎                          | 20 kB 36.3 MB/s eta 0:00:01\r\u001b[K     |███████▉                        | 30 kB 40.9 MB/s eta 0:00:01\r\u001b[K     |██████████▌                     | 40 kB 26.8 MB/s eta 0:00:01\r\u001b[K     |█████████████                   | 51 kB 21.1 MB/s eta 0:00:01\r\u001b[K     |███████████████▊                | 61 kB 24.0 MB/s eta 0:00:01\r\u001b[K     |██████████████████▎             | 71 kB 24.9 MB/s eta 0:00:01\r\u001b[K     |█████████████████████           | 81 kB 26.3 MB/s eta 0:00:01\r\u001b[K     |███████████████████████▌        | 92 kB 28.2 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████▏     | 102 kB 30.1 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████▊   | 112 kB 30.1 MB/s eta 0:00:01\r\u001b[K     |███████████████████████████████▍| 122 kB 30.1 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 125 kB 30.1 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": "zDeY6iVJgAx0",
        "outputId": "a0b56d2b-cc5e-4946-fa27-f8958d354840"
      },
      "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 30.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.16 in /usr/local/lib/python3.7/dist-packages (from POT) (1.21.6)\n",
            "Requirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.7/dist-packages (from POT) (1.7.3)\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": "J9f4yJdigGtM",
        "outputId": "1735582f-c658-4ca3-ca09-b79794d52788"
      },
      "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 26.4 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_NKL.py --root './data/NKL' --label './data/NKL' --save-dir './data/training/NKL_resize_100_100' --fixsize 400"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XnOWuIYVh3nE",
        "outputId": "ef7a073b-6f8c-43d7-ca78-93b396ed6701"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python train.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sRM97H0xQ4_O",
        "outputId": "b6a6d203-fcbe-4766-fa03-48de2a1a52ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2022-08-10 09:20:19,840 INFO {'DATA': {'DIR': 'data/training/', 'VAL_DIR': 'data/training/', 'TEST_DIR': 'data/NKL', 'LABEL_FILE': 'data/training/nkl_train.txt', 'VAL_LABEL_FILE': 'data/training/nkl_val.txt', 'TEST_LABEL_FILE': 'data/training/nkl_test.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 09:20:19,840 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 [00:00<00:00, 239MB/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 09:20:28,074 INFO Data loading done.\n",
            "2022-08-10 09:20:28,077 INFO Start training.\n",
            "  0% 0/1300 [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:0.004797791130840778: 100% 1300/1300 [17:18<00:00,  1.25it/s]\n",
            "100% 1300/1300 [01:11<00:00, 18.16it/s]\n",
            "2022-08-10 09:38:58,281 INFO Validation result: ==== Precision: 0.28916, Recall: 0.86127\n",
            "2022-08-10 09:38:58,282 INFO Validation result: ==== F-measure: 0.43296\n",
            "2022-08-10 09:38:58,282 INFO Validation result: ==== F-measure@0.95: 0.16845\n",
            "2022-08-10 09:39:00,485 INFO Epoch 0/30 finishied, auxiliaries saved to ./result/reproduce .\tElapsed 0 days 0 hours 18 minutes.\tRemaining 0 days 8 hours 57 minutes.\n",
            "Training Loss:0.005329909268766642: 100% 1300/1300 [17:17<00:00,  1.25it/s]\n",
            "100% 1300/1300 [01:10<00:00, 18.50it/s]\n",
            "2022-08-10 09:57:27,990 INFO Validation result: ==== Precision: 0.29298, Recall: 0.88016\n",
            "2022-08-10 09:57:27,991 INFO Validation result: ==== F-measure: 0.43963\n",
            "2022-08-10 09:57:27,991 INFO Validation result: ==== F-measure@0.95: 0.20074\n",
            "2022-08-10 09:57:30,025 INFO Epoch 1/30 finishied, auxiliaries saved to ./result/reproduce .\tElapsed 0 days 0 hours 37 minutes.\tRemaining 0 days 8 hours 38 minutes.\n",
            "Training Loss:0.005478281062096357: 100% 1300/1300 [17:17<00:00,  1.25it/s]\n",
            "100% 1300/1300 [01:06<00:00, 19.42it/s]\n",
            "2022-08-10 10:15:54,876 INFO Validation result: ==== Precision: 0.37907, Recall: 0.89518\n",
            "2022-08-10 10:15:54,877 INFO Validation result: ==== F-measure: 0.53260\n",
            "2022-08-10 10:15:54,877 INFO Validation result: ==== F-measure@0.95: 0.28177\n",
            "2022-08-10 10:15:57,137 INFO Epoch 2/30 finishied, auxiliaries saved to ./result/reproduce .\tElapsed 0 days 0 hours 55 minutes.\tRemaining 0 days 8 hours 19 minutes.\n",
            "Training Loss:0.0035464903339743614:  99% 1287/1300 [17:09<00:10,  1.25it/s]"
          ]
        }
      ]
    }
  ]
}