LGR_Net_colab.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "LGR-Net_colab.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "machine_shape": "hm",
      "mount_file_id": "1YS_Z687cLvuVVbqN-BPD_xjeR5BA6c4g",
      "authorship_tag": "ABX9TyPFg2AHllTNKaL1zNBcTlHe",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/DIPTE/Deep-Geometry-Learning-on-Colab/blob/master/LGR_Net_colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SVGLoqkARU4p"
      },
      "source": [
        "!ls"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1qMk4bnoSRzn",
        "outputId": "d56f0ac9-8de5-46a5-e7d7-ba53bd7c8393"
      },
      "source": [
        "!nvcc -V"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2020 NVIDIA Corporation\n",
            "Built on Wed_Jul_22_19:09:09_PDT_2020\n",
            "Cuda compilation tools, release 11.0, V11.0.221\n",
            "Build cuda_11.0_bu.TC445_37.28845127_0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h2dUHf8pSVec"
      },
      "source": [
        "!pip list"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EbGp0W_0SIxF"
      },
      "source": [
        "import os\n",
        "os.chdir('/content/drive/My Drive')#切换工作目录"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "37wvzfd9SNLn"
      },
      "source": [
        "!git clone https://github.com/sailor-z/LGR-Net.git"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rsVmBiQwSmWr"
      },
      "source": [
        "import os\n",
        "os.chdir('/content/drive/My Drive/LGR-Net')#切换工作目录"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "en_pNpRtTEt8"
      },
      "source": [
        "!sudo apt-get install build-essential python3-dev libssl-dev libffi-dev libxml2 libxml2-dev libxslt1-dev zlib1g-dev"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CkXnFJdoVCKb"
      },
      "source": [
        "!export CUDA_HOME=\"/usr/local/cuda/\"\n",
        "# export CUDA_HOME=/your/cuda/home/directory/\n",
        "# export LIBRARY_PATH=$LIBRARY_PATH:/your/cuda/lib64/  (optional)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1aQMBWC-SyJG",
        "outputId": "9e30fefe-b39c-4e1d-b7e8-18162a8815f1"
      },
      "source": [
        "!cd ./pt_utils/svd && python setup.py install\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "running install\n",
            "running bdist_egg\n",
            "running egg_info\n",
            "writing torch_batch_svd.egg-info/PKG-INFO\n",
            "writing dependency_links to torch_batch_svd.egg-info/dependency_links.txt\n",
            "writing top-level names to torch_batch_svd.egg-info/top_level.txt\n",
            "/usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:370: 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 'torch_batch_svd.egg-info/SOURCES.txt'\n",
            "installing library code to build/bdist.linux-x86_64/egg\n",
            "running install_lib\n",
            "running build_ext\n",
            "building 'torch_batch_svd' extension\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/cuda/include -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/include/python3.7m -c torch_batch_svd.cpp -o build/temp.linux-x86_64-3.7/torch_batch_svd.o -g -DDEBUG -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=torch_batch_svd -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/ATen/Parallel.h:140:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/utils.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/nn/cloneable.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/nn.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:13\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ParallelOpenMP.h:87:0:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kignoring #pragma omp parallel [\u001b[01;35m\u001b[K-Wunknown-pragmas\u001b[m\u001b[K]\n",
            " #pragma omp parallel for if ((end - begin) >= grain_size)\n",
            " \n",
            "\u001b[01m\u001b[Ktorch_batch_svd.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kstd::tuple<at::Tensor, at::Tensor, at::Tensor> torch_batch_svd::batch_svd_forward(at::Tensor, bool, double, int)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Ktorch_batch_svd.cpp:70:36:\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",
            "     const auto d_A = A.data<float>(\u001b[01;35m\u001b[K)\u001b[m\u001b[K;\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/ATen/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Context.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:501:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   T * \u001b[01;36m\u001b[Kdata\u001b[m\u001b[K() const {\n",
            "       \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ktorch_batch_svd.cpp:72:52:\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",
            "     auto s = at::empty({batch_size, minmn}, a.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K);\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/ATen/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Context.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:338:30:\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[Ktorch_batch_svd.cpp:73:30:\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",
            "     auto d_s = s.data<float>(\u001b[01;35m\u001b[K)\u001b[m\u001b[K;\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/ATen/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Context.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:501:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   T * \u001b[01;36m\u001b[Kdata\u001b[m\u001b[K() const {\n",
            "       \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ktorch_batch_svd.cpp:74:51:\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",
            "     auto U = at::empty({batch_size, m, m}, a.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K);\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/ATen/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Context.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:338:30:\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[Ktorch_batch_svd.cpp:75:36:\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",
            "     const auto d_U = U.data<float>(\u001b[01;35m\u001b[K)\u001b[m\u001b[K;\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/ATen/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Context.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:501:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   T * \u001b[01;36m\u001b[Kdata\u001b[m\u001b[K() const {\n",
            "       \u001b[01;36m\u001b[K^~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ktorch_batch_svd.cpp:77:51:\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",
            "     auto V = at::empty({batch_size, n, n}, a.type(\u001b[01;35m\u001b[K)\u001b[m\u001b[K);\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/ATen/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Context.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:338:30:\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[Ktorch_batch_svd.cpp:78:36:\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",
            "     const auto d_V = V.data<float>(\u001b[01;35m\u001b[K)\u001b[m\u001b[K;\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/ATen/Tensor.h:3:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Context.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9\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[Ktorch_batch_svd.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/TensorBody.h:501:7:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            "   T * \u001b[01;36m\u001b[Kdata\u001b[m\u001b[K() const {\n",
            "       \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 -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/torch_batch_svd.o -L/usr/local/lib/python3.7/dist-packages/torch/lib -lcusolver -lcublas -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-3.7/torch_batch_svd.cpython-37m-x86_64-linux-gnu.so\n",
            "creating build/bdist.linux-x86_64\n",
            "creating build/bdist.linux-x86_64/egg\n",
            "copying build/lib.linux-x86_64-3.7/torch_batch_svd.cpython-37m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n",
            "creating stub loader for torch_batch_svd.cpython-37m-x86_64-linux-gnu.so\n",
            "byte-compiling build/bdist.linux-x86_64/egg/torch_batch_svd.py to torch_batch_svd.cpython-37.pyc\n",
            "creating build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying torch_batch_svd.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying torch_batch_svd.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying torch_batch_svd.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying torch_batch_svd.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__.torch_batch_svd.cpython-37: module references __file__\n",
            "creating 'dist/torch_batch_svd-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 torch_batch_svd-0.0.0-py3.7-linux-x86_64.egg\n",
            "removing '/usr/local/lib/python3.7/dist-packages/torch_batch_svd-0.0.0-py3.7-linux-x86_64.egg' (and everything under it)\n",
            "creating /usr/local/lib/python3.7/dist-packages/torch_batch_svd-0.0.0-py3.7-linux-x86_64.egg\n",
            "Extracting torch_batch_svd-0.0.0-py3.7-linux-x86_64.egg to /usr/local/lib/python3.7/dist-packages\n",
            "torch-batch-svd 0.0.0 is already the active version in easy-install.pth\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/torch_batch_svd-0.0.0-py3.7-linux-x86_64.egg\n",
            "Processing dependencies for torch-batch-svd==0.0.0\n",
            "Finished processing dependencies for torch-batch-svd==0.0.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Egq4KovNdkuV",
        "outputId": "a3e15d3e-2078-4a15-c85c-f7a37c2d9b11"
      },
      "source": [
        "!cd ./pt_utils/svd && python test.py"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([[-0.4177, -0.4788,  0.4089],\n",
            "        [ 0.0152,  0.1507,  0.6869],\n",
            "        [ 0.2137, -0.8317,  0.5926],\n",
            "        [-0.4852,  0.0358,  0.4711],\n",
            "        [ 0.3797,  0.2507,  0.8463],\n",
            "        [-0.2151, -0.6489,  0.4648],\n",
            "        [ 0.5514,  0.0594,  0.8823],\n",
            "        [-0.2812, -0.1223,  0.5168],\n",
            "        [ 0.5919, -0.4246,  0.8158]], device='cuda:0')\n",
            "tensor([[-0.4177, -0.4788,  0.4089],\n",
            "        [ 0.0152,  0.1507,  0.6869],\n",
            "        [ 0.2137, -0.8317,  0.5926],\n",
            "        [-0.4852,  0.0358,  0.4711],\n",
            "        [ 0.3797,  0.2507,  0.8463],\n",
            "        [-0.2151, -0.6489,  0.4648],\n",
            "        [ 0.5514,  0.0594,  0.8823],\n",
            "        [-0.2812, -0.1223,  0.5168],\n",
            "        [ 0.5919, -0.4246,  0.8158]], device='cuda:0')\n",
            "tensor(-9.4064e-07, device='cuda:0', grad_fn=<SumBackward0>)\n",
            "False\n",
            "True\n",
            "False\n",
            "tensor([[-1.1258, -1.1524, -0.2506],\n",
            "        [-0.4339,  0.8487,  0.6920],\n",
            "        [-0.3160, -2.1152,  0.3223],\n",
            "        [-1.2633,  0.3500,  0.3081],\n",
            "        [ 0.1198,  1.2377,  1.1168],\n",
            "        [-0.2473, -1.3527, -1.6959],\n",
            "        [ 0.5667,  0.7935,  0.5988],\n",
            "        [-1.5551, -0.3414,  1.8530],\n",
            "        [ 0.7502, -0.5855, -0.1734]], device='cuda:0',\n",
            "       grad_fn=<SelectBackward>)\n",
            "tensor([[-1.1258, -1.1524, -0.2506],\n",
            "        [-0.4339,  0.8487,  0.6920],\n",
            "        [-0.3160, -2.1152,  0.3223],\n",
            "        [-1.2633,  0.3500,  0.3081],\n",
            "        [ 0.1198,  1.2377,  1.1168],\n",
            "        [-0.2473, -1.3527, -1.6959],\n",
            "        [ 0.5667,  0.7935,  0.5988],\n",
            "        [-1.5551, -0.3414,  1.8530],\n",
            "        [ 0.7502, -0.5855, -0.1734]], device='cuda:0', grad_fn=<MmBackward>)\n",
            "Finished\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XnCDBFiGZ3RQ"
      },
      "source": [
        "!pip install torch==1.4.0 torchvision==0.5.0"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tpp3p4KYgdPz",
        "outputId": "42635f95-42f7-48f0-a3ef-8dbd8c1e3b09"
      },
      "source": [
        "!pip install torch==1.9.0+cu102 torchvision==0.10.0+cu102 torchaudio===0.9.0 -f https://download.pytorch.org/whl/torch_stable.html"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
            "Collecting torch==1.9.0+cu102\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu102/torch-1.9.0%2Bcu102-cp37-cp37m-linux_x86_64.whl (831.4MB)\n",
            "\u001b[K     |████████████████████████████████| 831.4MB 20kB/s \n",
            "\u001b[?25hCollecting torchvision==0.10.0+cu102\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu102/torchvision-0.10.0%2Bcu102-cp37-cp37m-linux_x86_64.whl (22.1MB)\n",
            "\u001b[K     |████████████████████████████████| 22.1MB 226kB/s \n",
            "\u001b[?25hRequirement already satisfied: torchaudio===0.9.0 in /usr/local/lib/python3.7/dist-packages (0.9.0)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch==1.9.0+cu102) (3.7.4.3)\n",
            "Requirement already satisfied: pillow>=5.3.0 in /usr/local/lib/python3.7/dist-packages (from torchvision==0.10.0+cu102) (7.1.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torchvision==0.10.0+cu102) (1.19.5)\n",
            "Installing collected packages: torch, torchvision\n",
            "  Found existing installation: torch 1.9.0+cpu\n",
            "    Uninstalling torch-1.9.0+cpu:\n",
            "      Successfully uninstalled torch-1.9.0+cpu\n",
            "  Found existing installation: torchvision 0.10.0+cpu\n",
            "    Uninstalling torchvision-0.10.0+cpu:\n",
            "      Successfully uninstalled torchvision-0.10.0+cpu\n",
            "Successfully installed torch-1.9.0+cu102 torchvision-0.10.0+cu102\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yq4S_6sHbyR-",
        "outputId": "0133eda0-06cb-4b30-fb3e-9f0c23c7f320"
      },
      "source": [
        "!pip install torch===1.4.0+cu100 torchvision===0.5.0+cu100 -f https://download.pytorch.org/whl/torch_stable.html"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
            "Collecting torch===1.4.0+cu100\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu100/torch-1.4.0%2Bcu100-cp37-cp37m-linux_x86_64.whl (723.9MB)\n",
            "\u001b[K     |████████████████████████████████| 723.9MB 24kB/s \n",
            "\u001b[?25hCollecting torchvision===0.5.0+cu100\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu100/torchvision-0.5.0%2Bcu100-cp37-cp37m-linux_x86_64.whl (4.0MB)\n",
            "\u001b[K     |████████████████████████████████| 4.0MB 43.6MB/s \n",
            "\u001b[?25hRequirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision===0.5.0+cu100) (7.1.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from torchvision===0.5.0+cu100) (1.15.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torchvision===0.5.0+cu100) (1.19.5)\n",
            "\u001b[31mERROR: torchtext 0.10.0 has requirement torch==1.9.0, but you'll have torch 1.4.0+cu100 which is incompatible.\u001b[0m\n",
            "Installing collected packages: torch, torchvision\n",
            "  Found existing installation: torch 1.4.0\n",
            "    Uninstalling torch-1.4.0:\n",
            "      Successfully uninstalled torch-1.4.0\n",
            "  Found existing installation: torchvision 0.5.0\n",
            "    Uninstalling torchvision-0.5.0:\n",
            "      Successfully uninstalled torchvision-0.5.0\n",
            "Successfully installed torch-1.4.0+cu100 torchvision-0.5.0+cu100\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZmvqWGRodwhj",
        "outputId": "03dc2ba0-2388-456e-8434-e62db369530d"
      },
      "source": [
        "!python ./train_cls.py"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Namespace(SO3=True, batchSize=32, bias=False, decay_rate=0.7, decay_step=100, eval=False, gpu_num='1', knn=32, load=False, lr=0.001, model='./logs/', momentum=0.9, nepoch=300, num_points=1024, outf='./logs/', reg_weight=0.0001, test_interval=1, use_sgd=True, workers=4)\n",
            "Random Seed:  7230\n",
            "Using GPU : 1\n",
            "dataset_len: 9840\n",
            "Use SGD\n",
            "/usr/local/lib/python3.7/dist-packages/torch/optim/lr_scheduler.py:134: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n",
            "  \"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\", UserWarning)\n",
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at  /pytorch/c10/core/TensorImpl.h:1156.)\n",
            "  return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)\n",
            "Train 0, loss: 2.800216, train acc: 0.418160\n",
            "Test :: test acc: 0.495948\n",
            "Train 1, loss: 2.259420, train acc: 0.605965\n",
            "Test :: test acc: 0.651135\n",
            "Train 2, loss: 2.109015, train acc: 0.680273\n",
            "Test :: test acc: 0.726094\n",
            "Train 3, loss: 2.034706, train acc: 0.709589\n",
            "Test :: test acc: 0.754052\n",
            "Train 4, loss: 1.962007, train acc: 0.752443\n",
            "Test :: test acc: 0.773501\n",
            "Train 5, loss: 1.906256, train acc: 0.772089\n",
            "Test :: test acc: 0.781199\n",
            "Train 6, loss: 1.871032, train acc: 0.785932\n",
            "Test :: test acc: 0.783225\n",
            "Train 7, loss: 1.842157, train acc: 0.799674\n",
            "Test :: test acc: 0.781605\n",
            "Train 8, loss: 1.828415, train acc: 0.805069\n",
            "Test :: test acc: 0.810373\n",
            "Train 9, loss: 1.791655, train acc: 0.822985\n",
            "Test :: test acc: 0.839546\n",
            "Train 10, loss: 1.773058, train acc: 0.832146\n",
            "Test :: test acc: 0.819692\n",
            "Train 11, loss: 1.761915, train acc: 0.832553\n",
            "Test :: test acc: 0.806726\n",
            "Train 12, loss: 1.748175, train acc: 0.839373\n",
            "Test :: test acc: 0.847650\n",
            "Train 13, loss: 1.729401, train acc: 0.847516\n",
            "Test :: test acc: 0.824959\n",
            "Train 14, loss: 1.715524, train acc: 0.856372\n",
            "Test :: test acc: 0.848460\n",
            "Train 15, loss: 1.707187, train acc: 0.856474\n",
            "Test :: test acc: 0.852512\n",
            "Train 16, loss: 1.699756, train acc: 0.859121\n",
            "Test :: test acc: 0.851702\n",
            "Train 17, loss: 1.690161, train acc: 0.866246\n",
            "Test :: test acc: 0.854943\n",
            "Train 18, loss: 1.681962, train acc: 0.869401\n",
            "Test :: test acc: 0.834684\n",
            "Train 19, loss: 1.669559, train acc: 0.871641\n",
            "Test :: test acc: 0.861021\n",
            "Train 20, loss: 1.669173, train acc: 0.871437\n",
            "Test :: test acc: 0.852512\n",
            "Train 21, loss: 1.658156, train acc: 0.875611\n",
            "Test :: test acc: 0.837520\n",
            "Train 22, loss: 1.654197, train acc: 0.878563\n",
            "Test :: test acc: 0.803079\n",
            "Train 23, loss: 1.648564, train acc: 0.880700\n",
            "Test :: test acc: 0.850891\n",
            "Train 24, loss: 1.643410, train acc: 0.884059\n",
            "Test :: test acc: 0.797002\n",
            "Train 25, loss: 1.642583, train acc: 0.882838\n",
            "Test :: test acc: 0.858590\n",
            "Train 26, loss: 1.629302, train acc: 0.892101\n",
            "Test :: test acc: 0.841977\n",
            "Train 27, loss: 1.628725, train acc: 0.891287\n",
            "Test :: test acc: 0.838331\n",
            "Train 28, loss: 1.621262, train acc: 0.889149\n",
            "Test :: test acc: 0.868314\n",
            "Train 29, loss: 1.620710, train acc: 0.893831\n",
            "Test :: test acc: 0.865883\n",
            "Train 30, loss: 1.611703, train acc: 0.893831\n",
            "Test :: test acc: 0.858995\n",
            "Train 31, loss: 1.608465, train acc: 0.893730\n",
            "Test :: test acc: 0.845219\n",
            "Train 32, loss: 1.611572, train acc: 0.895257\n",
            "Test :: test acc: 0.866694\n",
            "Train 33, loss: 1.605718, train acc: 0.896173\n",
            "Test :: test acc: 0.854943\n",
            "Train 34, loss: 1.591988, train acc: 0.906148\n",
            "Test :: test acc: 0.871556\n",
            "Train 35, loss: 1.589916, train acc: 0.904214\n",
            "Test :: test acc: 0.850081\n",
            "Train 36, loss: 1.591425, train acc: 0.902687\n",
            "Test :: test acc: 0.856564\n",
            "Train 37, loss: 1.587383, train acc: 0.903298\n",
            "Test :: test acc: 0.834279\n",
            "Train 38, loss: 1.580591, train acc: 0.907268\n",
            "Test :: test acc: 0.869530\n",
            "Train 39, loss: 1.577075, train acc: 0.908388\n",
            "Test :: test acc: 0.856564\n",
            "Train 40, loss: 1.579292, train acc: 0.907879\n",
            "Test :: test acc: 0.859400\n",
            "Train 41, loss: 1.576309, train acc: 0.908795\n",
            "Test :: test acc: 0.859400\n",
            "Train 42, loss: 1.573819, train acc: 0.910627\n",
            "Test :: test acc: 0.874392\n",
            "Train 43, loss: 1.578392, train acc: 0.906861\n",
            "Test :: test acc: 0.828201\n",
            "Train 44, loss: 1.571994, train acc: 0.910932\n",
            "Test :: test acc: 0.856159\n",
            "Train 45, loss: 1.567371, train acc: 0.915615\n",
            "Test :: test acc: 0.857374\n",
            "Train 46, loss: 1.565503, train acc: 0.914597\n",
            "Test :: test acc: 0.884522\n",
            "Train 47, loss: 1.566172, train acc: 0.913986\n",
            "Test :: test acc: 0.857780\n",
            "Train 48, loss: 1.563042, train acc: 0.917243\n",
            "Test :: test acc: 0.884522\n",
            "Train 49, loss: 1.560418, train acc: 0.915513\n",
            "Test :: test acc: 0.871961\n",
            "Train 50, loss: 1.557208, train acc: 0.915717\n",
            "Test :: test acc: 0.863452\n",
            "Train 51, loss: 1.553143, train acc: 0.916022\n",
            "Test :: test acc: 0.844408\n",
            "Train 52, loss: 1.548388, train acc: 0.917651\n",
            "Test :: test acc: 0.848055\n",
            "Train 53, loss: 1.548627, train acc: 0.922435\n",
            "Test :: test acc: 0.852107\n",
            "Train 54, loss: 1.550262, train acc: 0.918363\n",
            "Test :: test acc: 0.855754\n",
            "Train 55, loss: 1.539940, train acc: 0.921519\n",
            "Test :: test acc: 0.858590\n",
            "Train 56, loss: 1.542373, train acc: 0.924064\n",
            "Test :: test acc: 0.866694\n",
            "Train 57, loss: 1.541484, train acc: 0.919686\n",
            "Test :: test acc: 0.856969\n",
            "Train 58, loss: 1.532582, train acc: 0.926710\n",
            "Test :: test acc: 0.871556\n",
            "Train 59, loss: 1.538116, train acc: 0.928339\n",
            "Test :: test acc: 0.849676\n",
            "Train 60, loss: 1.538972, train acc: 0.921824\n",
            "Test :: test acc: 0.836710\n",
            "Train 61, loss: 1.535215, train acc: 0.925692\n",
            "Test :: test acc: 0.882091\n",
            "Train 62, loss: 1.530770, train acc: 0.927423\n",
            "Test :: test acc: 0.846434\n",
            "Train 63, loss: 1.530220, train acc: 0.928033\n",
            "Test :: test acc: 0.844408\n",
            "Train 64, loss: 1.524582, train acc: 0.927830\n",
            "Test :: test acc: 0.856969\n",
            "Train 65, loss: 1.526371, train acc: 0.929764\n",
            "Test :: test acc: 0.850486\n",
            "Train 66, loss: 1.521541, train acc: 0.931291\n",
            "Test :: test acc: 0.860616\n",
            "Train 67, loss: 1.514825, train acc: 0.935057\n",
            "Test :: test acc: 0.861021\n",
            "Train 68, loss: 1.517734, train acc: 0.936177\n",
            "Test :: test acc: 0.830632\n",
            "Train 69, loss: 1.523396, train acc: 0.928441\n",
            "Test :: test acc: 0.851702\n",
            "Train 70, loss: 1.523962, train acc: 0.929866\n",
            "Test :: test acc: 0.879660\n",
            "Train 71, loss: 1.516554, train acc: 0.931901\n",
            "Test :: test acc: 0.882901\n",
            "Train 72, loss: 1.519398, train acc: 0.929153\n",
            "Test :: test acc: 0.863857\n",
            "Train 73, loss: 1.514382, train acc: 0.934039\n",
            "Test :: test acc: 0.840762\n",
            "Train 74, loss: 1.513308, train acc: 0.935566\n",
            "Test :: test acc: 0.867504\n",
            "Train 75, loss: 1.516537, train acc: 0.932003\n",
            "Test :: test acc: 0.860211\n",
            "Train 76, loss: 1.506191, train acc: 0.936177\n",
            "Test :: test acc: 0.850081\n",
            "Train 77, loss: 1.518290, train acc: 0.931087\n",
            "Test :: test acc: 0.865073\n",
            "Train 78, loss: 1.504707, train acc: 0.935566\n",
            "Test :: test acc: 0.882091\n",
            "Train 79, loss: 1.498927, train acc: 0.936889\n",
            "Test :: test acc: 0.872366\n",
            "Train 80, loss: 1.506970, train acc: 0.935566\n",
            "Test :: test acc: 0.866288\n",
            "Train 81, loss: 1.494399, train acc: 0.942895\n",
            "Test :: test acc: 0.844814\n",
            "Train 82, loss: 1.496692, train acc: 0.939129\n",
            "Test :: test acc: 0.865883\n",
            "Train 83, loss: 1.489626, train acc: 0.943506\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jokUNqdZjqCI"
      },
      "source": [
        "!sudo rm /var/lib/apt/lists/* -vf\n",
        "!sudo apt-get update\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JkNFOYaGkguH",
        "outputId": "8464c03f-9535-467b-d716-ae92a2867bee"
      },
      "source": [
        "import torch\n",
        "print(torch.cuda.is_available())\n",
        "print(torch.cuda.device_count())\n",
        "print(torch.cuda.get_device_name())\n",
        "print(torch.cuda.current_device())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "True\n",
            "1\n",
            "Tesla P100-PCIE-16GB\n",
            "0\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}