From 46a2cde85dda34a0c95addf27382258e2d67e28b Mon Sep 17 00:00:00 2001 From: Alpha Date: Sat, 21 Mar 2020 21:43:32 -0400 Subject: [PATCH 1/8] Several changes that allow manual resuming - Improved Collab notebook readme cell - Added configuration for `FRAME_INPUT_DIR` - Added configuration for `FRAME_OUTPUT_DIR` - Showing a bit more info about the GPU Card (some drivers might actually not run) - Fixed git clone directory path - Passing `start_frame` and `end_frame` as parameters to the python script (to allow for resuming runs) - Avoid outputs middle-steps --- Colab_DAIN_alpha.ipynb | 2756 +++++++++++++++++++++++++++++--- colab_MiddleBury_slowmotion.py | 16 +- my_args.py | 6 + 3 files changed, 2508 insertions(+), 270 deletions(-) diff --git a/Colab_DAIN_alpha.ipynb b/Colab_DAIN_alpha.ipynb index 2d6a3a2..29823cd 100644 --- a/Colab_DAIN_alpha.ipynb +++ b/Colab_DAIN_alpha.ipynb @@ -3,7 +3,7 @@ "nbformat_minor": 0, "metadata": { "colab": { - "name": "Colab_DAIN_alpha 0.2.ipynb", + "name": "Colab_DAIN_alpha.ipynb", "provenance": [], "collapsed_sections": [], "toc_visible": true @@ -38,16 +38,19 @@ "My fork:\n", "https://github.com/styler00dollar/DAIN\n", "\n", - "Enhancement by Styler00Dollar aka \"sudo rm -rf / --no-preserve-root#8353\" on discord and Alpha. Please do not run this command in your linux terminal. It's rather meant as a joke.\n", + "Enhancement by [Styler00Dollar](https://github.com/styler00dollar) aka \"sudo rm -rf / --no-preserve-root#8353\" on discord and [Alpha](https://github.com/AlphaGit). Please do not run this command in your linux terminal. It's rather meant as a joke.\n", "\n", "A simple guide:\n", "- Copy the .ipynb-file to your drive.\n", "- Create a folder inside of Google Drive named \"DAIN\"\n", - "- Don't forget to configure the filename in Colab. You will notice that down below.\n", + "- Change the configurations in the next cell\n", + "- Run cells one by one\n", "\n", "Stuff that should be improved:\n", "- Gif (RGBA24 or alpha in general) is currently not supported.\n", - "- Adding menu to select speed." + "- Adding configuration to select speed.\n", + "- Detect scenes to avoid interpolating scene-changes\n", + "- Auto-resume" ] }, { @@ -64,15 +67,25 @@ "# Input file: Path (relative to the root of your Google Drive) to the input file.\n", "# For instance, if you save your \"example.mkv\" file in your Google Drive, inside a \"videos\" folder, the path would be:\n", "# videos/example.mkv\n", - "INPUT_FILEPATH = \"DAIN/input.mp4\"\n", + "INPUT_FILEPATH = \"DAIN/batmanIn.mp4\"\n", + "\n", + "# Output file path: path (relative to the root of your Google Drive) for the output file.\n", + "# Extension should always be MP4.\n", + "OUTPUT_FILE_PATH = \"DAIN/batmanOut.mp4\"\n", "\n", "# Target FPS = how many frames per second should the result have. This will determine how many intermediate images are\n", "# interpolated.\n", "TARGET_FPS = 60\n", "\n", - "# Output file path: path (relative to the root of your Google Drive) for the output file.\n", - "# Extension should always be MKV.\n", - "OUTPUT_FILE_PATH = \"DAIN/output.mkv\"" + "# Frame input directly\n", + "# Use a path that is in your GDrive if you already have the list of frames in the format 00001.png, 00002.png, etc.\n", + "# Your GDrive is located at `/content/gdrive/My Drive/`\n", + "FRAME_INPUT_DIR = '/content/DAIN/input_frames'\n", + "\n", + "# Frame output directory\n", + "# Use a location in your GDrive if you want the generated frames stored to your Google Drive.\n", + "# Your GDrive is located at `/content/gdrive/My Drive/DAIN/tmp`\n", + "FRAME_OUTPUT_DIR = '/content/DAIN/output_frames'" ], "execution_count": 0, "outputs": [] @@ -82,7 +95,7 @@ "metadata": { "id": "N9cGwalNeyk9", "colab_type": "code", - "outputId": "9f73f458-8b61-4d6d-d7dc-fc496d5f8b44", + "outputId": "27db4400-af63-4939-a3f5-8814c3a9c352", "colab": { "base_uri": "https://localhost:8080/", "height": 139 @@ -93,10 +106,9 @@ "\n", "from google.colab import drive\n", "drive.mount('/content/gdrive')\n", - "model_dir = '/content/gdrive/My Drive/DAIN/'\n", "print('Google Drive connected.')" ], - "execution_count": 0, + "execution_count": 3, "outputs": [ { "output_type": "stream", @@ -117,10 +129,10 @@ "metadata": { "id": "irzjv1x4e3S4", "colab_type": "code", - "outputId": "0c89ef56-bd59-43fa-d003-d6c9a737c9b0", + "outputId": "7abe5d31-dc8b-49a8-8cbd-5211f36c9224", "colab": { "base_uri": "https://localhost:8080/", - "height": 34 + "height": 51 } }, "source": [ @@ -131,36 +143,49 @@ "# P4: 8GB (Not tested.)\n", "# K80: 8GB (Not tested.)\n", "\n", - "!nvidia-smi --query-gpu=gpu_name --format=csv,noheader" + "!nvidia-smi --query-gpu=gpu_name,driver_version,memory.total --format=csv" ], - "execution_count": 0, + "execution_count": 4, "outputs": [ { "output_type": "stream", "text": [ - "Tesla P100-PCIE-16GB\n" + "name, driver_version, memory.total [MiB]\n", + "Tesla P4, 418.67, 7611 MiB\n" ], "name": "stdout" } ] }, + { + "cell_type": "markdown", + "metadata": { + "id": "UYHTTP91oMvh", + "colab_type": "text" + }, + "source": [ + "# Install dependencies.\n", + "\n", + "This next step may take somewhere between 15-20 minutes.\n", + "\n", + "Look for the \"Restart\" warning when it finishes, but **do not restart** the notebook.\n" + ] + }, { "cell_type": "code", "metadata": { "id": "UeaU8um5-2NS", "colab_type": "code", - "outputId": "40a7acd6-2cfa-4ea2-d0e3-ca8941d98900", + "outputId": "87f6e761-1839-4510-8f2a-d58d11886ab2", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 } }, "source": [ - "#@title Inititialization (Run this once at startup. Approximately 15-20 Minutes.)\n", - "\n", "from IPython.display import clear_output\n", "!rm -rf /content/DAIN\n", - "!git clone https://github.com/styler00dollar/Colab-DAIN\n", + "!git clone https://github.com/styler00dollar/Colab-DAIN /content/DAIN\n", "\n", "# This takes a while. Just wait. ~15 minutes.\n", "# Building DAIN.\n", @@ -196,33 +221,2406 @@ "\n", "!pip install --force-reinstall scipy==1.0.0" ], - "execution_count": 0, + "execution_count": 5, "outputs": [ { "output_type": "stream", "text": [ + "Cloning into '/content/DAIN'...\n", + "remote: Enumerating objects: 636, done.\u001b[K\n", + "remote: Total 636 (delta 0), reused 0 (delta 0), pack-reused 636\n", + "Receiving objects: 100% (636/636), 230.82 KiB | 321.00 KiB/s, done.\n", + "Resolving deltas: 100% (358/358), done.\n", + "/content/DAIN/my_package\n", + "Need pytorch>=1.0.0\n", + "./build.sh: line 4: activate: No such file or directory\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating mindepthflowprojection_cuda.egg-info\n", + "writing mindepthflowprojection_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to mindepthflowprojection_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to mindepthflowprojection_cuda.egg-info/top_level.txt\n", + "writing manifest file 'mindepthflowprojection_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'mindepthflowprojection_cuda.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 'mindepthflowprojection_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c mindepthflowprojection_cuda.cc -o build/temp.linux-x86_64-3.6/mindepthflowprojection_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=mindepthflowprojection_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c mindepthflowprojection_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/mindepthflowprojection_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=mindepthflowprojection_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(73): warning: variable \"ix2_R\" was declared but never referenced\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(74): warning: variable \"iy2_B\" was declared but never referenced\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(73): warning: variable \"ix2_R\" was declared but never referenced\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(74): warning: variable \"iy2_B\" was declared but never referenced\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(73): warning: variable \"ix2_R\" was declared but never referenced\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(74): warning: variable \"iy2_B\" was declared but never referenced\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(73): warning: variable \"ix2_R\" was declared but never referenced\n", + "\n", + "mindepthflowprojection_cuda_kernel.cu(74): warning: variable \"iy2_B\" was declared but never referenced\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:344:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:344:548:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:344:575:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:344:601:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:344:628:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:344:1069:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:344:1095:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:344:1120:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:344:1146:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:381:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:381:534:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:381:561:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:381:587:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:381:614:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:381:1041:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:381:1067:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:381:1092:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:381:1118:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:439:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:439:549:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:576:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:602:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:629:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:660:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:691:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:722:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kmindepthflowprojection_cuda_kernel.cu:439:1164:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:1190:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:1215:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:1241:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:1271:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:1301:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kmindepthflowprojection_cuda_kernel.cu:439:1331:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"minDepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/mindepthflowprojection_cuda.o build/temp.linux-x86_64-3.6/mindepthflowprojection_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/mindepthflowprojection_cuda.cpython-36m-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_64-3.6/mindepthflowprojection_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for mindepthflowprojection_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/mindepthflowprojection_cuda.py to mindepthflowprojection_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying mindepthflowprojection_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying mindepthflowprojection_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying mindepthflowprojection_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying mindepthflowprojection_cuda.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__.mindepthflowprojection_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/mindepthflowprojection_cuda-0.0.0-py3.6-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 mindepthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/mindepthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting mindepthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding mindepthflowprojection-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/mindepthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for mindepthflowprojection-cuda==0.0.0\n", + "Finished processing dependencies for mindepthflowprojection-cuda==0.0.0\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating flowprojection_cuda.egg-info\n", + "writing flowprojection_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to flowprojection_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to flowprojection_cuda.egg-info/top_level.txt\n", + "writing manifest file 'flowprojection_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'flowprojection_cuda.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 'flowprojection_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c flowprojection_cuda.cc -o build/temp.linux-x86_64-3.6/flowprojection_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=flowprojection_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c flowprojection_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/flowprojection_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=flowprojection_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:332:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:332:472:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:332:498:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:332:525:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:332:890:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:332:915:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:332:941:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:350:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjectionAveraging_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:350:469:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjectionAveraging_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:350:495:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjectionAveraging_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:350:522:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjectionAveraging_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:350:884:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjectionAveraging_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:350:909:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjectionAveraging_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:350:935:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjectionAveraging_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:377:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowFillhole_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:377:458:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowFillhole_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:377:484:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowFillhole_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:377:511:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowFillhole_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:377:862:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowFillhole_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:377:887:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowFillhole_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:377:913:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowFillhole_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:432:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:432:473:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:432:499:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:432:530:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:432:561:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kflowprojection_cuda_kernel.cu:432:927:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:432:952:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:432:982:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kflowprojection_cuda_kernel.cu:432:1012:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"FlowProjection_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/flowprojection_cuda.o build/temp.linux-x86_64-3.6/flowprojection_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/flowprojection_cuda.cpython-36m-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_64-3.6/flowprojection_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for flowprojection_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/flowprojection_cuda.py to flowprojection_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying flowprojection_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying flowprojection_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying flowprojection_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying flowprojection_cuda.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__.flowprojection_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/flowprojection_cuda-0.0.0-py3.6-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 flowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/flowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting flowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding flowprojection-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/flowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for flowprojection-cuda==0.0.0\n", + "Finished processing dependencies for flowprojection-cuda==0.0.0\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating separableconv_cuda.egg-info\n", + "writing separableconv_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to separableconv_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to separableconv_cuda.egg-info/top_level.txt\n", + "writing manifest file 'separableconv_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'separableconv_cuda.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 'separableconv_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c separableconv_cuda.cc -o build/temp.linux-x86_64-3.6/separableconv_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=separableconv_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c separableconv_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/separableconv_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=separableconv_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:167:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:167:629:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:167:656:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:167:683:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:167:710:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:167:1232:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:167:1258:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:167:1284:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:167:1310:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:228:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:228:630:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:657:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:684:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:715:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:746:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:777:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:808:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconv_cuda_kernel.cu:228:1331:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:1357:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:1383:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:1413:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:1443:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:1473:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconv_cuda_kernel.cu:228:1503:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/separableconv_cuda.o build/temp.linux-x86_64-3.6/separableconv_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/separableconv_cuda.cpython-36m-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_64-3.6/separableconv_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for separableconv_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/separableconv_cuda.py to separableconv_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconv_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconv_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconv_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconv_cuda.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__.separableconv_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/separableconv_cuda-0.0.0-py3.6-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 separableconv_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/separableconv_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting separableconv_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding separableconv-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/separableconv_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for separableconv-cuda==0.0.0\n", + "Finished processing dependencies for separableconv-cuda==0.0.0\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating interpolationch_cuda.egg-info\n", + "writing interpolationch_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to interpolationch_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to interpolationch_cuda.egg-info/top_level.txt\n", + "writing manifest file 'interpolationch_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'interpolationch_cuda.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 'interpolationch_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c interpolationch_cuda.cc -o build/temp.linux-x86_64-3.6/interpolationch_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=interpolationch_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c interpolationch_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/interpolationch_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=interpolationch_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:237:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:237:482:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:237:509:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:237:536:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:237:911:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:237:937:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:237:963:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_forward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:291:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] \u001b[01;35m\u001b[K{\u001b[m\u001b[K\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:291:483:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:510:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:541:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:572:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:603:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolationch_cuda_kernel.cu:291:979:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:1005:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:1035:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:1065:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolationch_cuda_kernel.cu:291:1095:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"InterpolationChLayer_gpu_backward_kernelfunc\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/interpolationch_cuda.o build/temp.linux-x86_64-3.6/interpolationch_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/interpolationch_cuda.cpython-36m-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_64-3.6/interpolationch_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for interpolationch_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/interpolationch_cuda.py to interpolationch_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolationch_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolationch_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolationch_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolationch_cuda.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__.interpolationch_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/interpolationch_cuda-0.0.0-py3.6-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 interpolationch_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/interpolationch_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting interpolationch_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding interpolationch-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/interpolationch_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for interpolationch-cuda==0.0.0\n", + "Finished processing dependencies for interpolationch-cuda==0.0.0\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating depthflowprojection_cuda.egg-info\n", + "writing depthflowprojection_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to depthflowprojection_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to depthflowprojection_cuda.egg-info/top_level.txt\n", + "writing manifest file 'depthflowprojection_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'depthflowprojection_cuda.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 'depthflowprojection_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c depthflowprojection_cuda.cc -o build/temp.linux-x86_64-3.6/depthflowprojection_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=depthflowprojection_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c depthflowprojection_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/depthflowprojection_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=depthflowprojection_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:373:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:373:545:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:373:572:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:373:598:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:373:625:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:373:1063:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:373:1089:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:373:1114:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:373:1140:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:395:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:395:542:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:395:569:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:395:595:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:395:622:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:395:1057:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:395:1083:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:395:1108:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:395:1134:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjectionAveraging\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:423:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:423:531:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:423:558:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:423:584:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:423:611:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:423:1035:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:423:1061:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:423:1086:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:423:1112:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowFillhole\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:481:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:481:546:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:573:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:599:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:626:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:657:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:688:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:719:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kdepthflowprojection_cuda_kernel.cu:481:1158:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:1184:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:1209:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:1235:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:1265:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:1295:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kdepthflowprojection_cuda_kernel.cu:481:1325:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/depthflowprojection_cuda.o build/temp.linux-x86_64-3.6/depthflowprojection_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/depthflowprojection_cuda.cpython-36m-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_64-3.6/depthflowprojection_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for depthflowprojection_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/depthflowprojection_cuda.py to depthflowprojection_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying depthflowprojection_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying depthflowprojection_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying depthflowprojection_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying depthflowprojection_cuda.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__.depthflowprojection_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/depthflowprojection_cuda-0.0.0-py3.6-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 depthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/depthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting depthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding depthflowprojection-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/depthflowprojection_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for depthflowprojection-cuda==0.0.0\n", + "Finished processing dependencies for depthflowprojection-cuda==0.0.0\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating interpolation_cuda.egg-info\n", + "writing interpolation_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to interpolation_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to interpolation_cuda.egg-info/top_level.txt\n", + "writing manifest file 'interpolation_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'interpolation_cuda.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 'interpolation_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c interpolation_cuda.cc -o build/temp.linux-x86_64-3.6/interpolation_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=interpolation_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c interpolation_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/interpolation_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=interpolation_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:235:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:235:480:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:235:507:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:235:534:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:235:907:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:235:933:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:235:959:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:290:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:290:481:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:508:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:539:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:570:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:601:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kinterpolation_cuda_kernel.cu:290:975:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:1001:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:1031:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:1061:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kinterpolation_cuda_kernel.cu:290:1091:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/interpolation_cuda.o build/temp.linux-x86_64-3.6/interpolation_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/interpolation_cuda.cpython-36m-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_64-3.6/interpolation_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for interpolation_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/interpolation_cuda.py to interpolation_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolation_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolation_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolation_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying interpolation_cuda.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__.interpolation_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/interpolation_cuda-0.0.0-py3.6-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 interpolation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/interpolation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting interpolation_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding interpolation-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/interpolation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for interpolation-cuda==0.0.0\n", + "Finished processing dependencies for interpolation-cuda==0.0.0\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating separableconvflow_cuda.egg-info\n", + "writing separableconvflow_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to separableconvflow_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to separableconvflow_cuda.egg-info/top_level.txt\n", + "writing manifest file 'separableconvflow_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'separableconvflow_cuda.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 'separableconvflow_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c separableconvflow_cuda.cc -o build/temp.linux-x86_64-3.6/separableconvflow_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=separableconvflow_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c separableconvflow_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/separableconvflow_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=separableconvflow_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:206:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:206:653:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:206:680:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:206:707:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:206:739:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:206:1285:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:206:1311:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:206:1337:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:206:1368:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:268:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:268:654:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:681:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:708:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:744:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:775:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:806:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:837:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kseparableconvflow_cuda_kernel.cu:268:1384:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:1410:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:1436:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:1471:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:1501:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:1531:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kseparableconvflow_cuda_kernel.cu:268:1561:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/separableconvflow_cuda.o build/temp.linux-x86_64-3.6/separableconvflow_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/separableconvflow_cuda.cpython-36m-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_64-3.6/separableconvflow_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for separableconvflow_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/separableconvflow_cuda.py to separableconvflow_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconvflow_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconvflow_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconvflow_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying separableconvflow_cuda.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__.separableconvflow_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/separableconvflow_cuda-0.0.0-py3.6-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 separableconvflow_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/separableconvflow_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting separableconvflow_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding separableconvflow-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/separableconvflow_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for separableconvflow-cuda==0.0.0\n", + "Finished processing dependencies for separableconvflow-cuda==0.0.0\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating filterinterpolation_cuda.egg-info\n", + "writing filterinterpolation_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to filterinterpolation_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to filterinterpolation_cuda.egg-info/top_level.txt\n", + "writing manifest file 'filterinterpolation_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'filterinterpolation_cuda.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 'filterinterpolation_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c filterinterpolation_cuda.cc -o build/temp.linux-x86_64-3.6/filterinterpolation_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=filterinterpolation_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c filterinterpolation_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/filterinterpolation_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=filterinterpolation_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:492:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:492:567:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:492:594:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:492:621:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:492:648:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:492:1108:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:492:1134:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:492:1160:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:492:1186:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:551:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:551:568:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:595:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:622:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:653:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:684:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:715:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:746:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kfilterinterpolation_cuda_kernel.cu:551:1207:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:1233:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:1259:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:1289:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:1319:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:1349:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kfilterinterpolation_cuda_kernel.cu:551:1379:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES(input1.type(), \"DepthFlowProjection_gpu_backward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/filterinterpolation_cuda.o build/temp.linux-x86_64-3.6/filterinterpolation_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/filterinterpolation_cuda.cpython-36m-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_64-3.6/filterinterpolation_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for filterinterpolation_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/filterinterpolation_cuda.py to filterinterpolation_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying filterinterpolation_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying filterinterpolation_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying filterinterpolation_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying filterinterpolation_cuda.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__.filterinterpolation_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/filterinterpolation_cuda-0.0.0-py3.6-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 filterinterpolation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/filterinterpolation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting filterinterpolation_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding filterinterpolation-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/filterinterpolation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for filterinterpolation-cuda==0.0.0\n", + "Finished processing dependencies for filterinterpolation-cuda==0.0.0\n", "Building #1 done.\n", - "/content/DAIN/PWCNet/correlation_package_pytorch1_0\n" + "/content/DAIN/PWCNet/correlation_package_pytorch1_0\n", + "Need pytorch>=1.0.0\n", + "./build.sh: line 4: activate: No such file or directory\n", + "running install\n", + "running bdist_egg\n", + "running egg_info\n", + "creating correlation_cuda.egg-info\n", + "writing correlation_cuda.egg-info/PKG-INFO\n", + "writing dependency_links to correlation_cuda.egg-info/dependency_links.txt\n", + "writing top-level names to correlation_cuda.egg-info/top_level.txt\n", + "writing manifest file 'correlation_cuda.egg-info/SOURCES.txt'\n", + "writing manifest file 'correlation_cuda.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 'correlation_cuda' extension\n", + "creating build\n", + "creating build/temp.linux-x86_64-3.6\n", + "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c correlation_cuda.cc -o build/temp.linux-x86_64-3.6/correlation_cuda.o -std=c++11 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=correlation_cuda -D_GLIBCXX_USE_CXX11_ABI=0\n", + "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c correlation_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/correlation_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=correlation_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n", + "\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:386:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"channels_first_fwd_1\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:386:317:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"channels_first_fwd_1\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:386:345:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"channels_first_fwd_1\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:386:605:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"channels_first_fwd_1\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:386:632:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"channels_first_fwd_1\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:386:903:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"channels_first_fwd_1\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:386:934:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"channels_first_fwd_1\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:393:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"channels_first_fwd_2\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:393:317:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"channels_first_fwd_2\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:393:345:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"channels_first_fwd_2\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:393:605:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"channels_first_fwd_2\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:393:632:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"channels_first_fwd_2\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:393:903:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"channels_first_fwd_2\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:393:934:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"channels_first_fwd_2\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:403:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:403:328:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:403:400:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:403:469:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:403:748:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:403:819:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:403:887:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:403:1177:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:403:1252:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:403:1324:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"correlation_forward\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:495:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:495:317:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:495:345:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:495:605:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:495:632:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:495:903:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:495:934:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:507:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:507:317:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:507:345:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:507:605:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:507:632:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:507:903:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:507:934:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:524:99:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:524:343:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:524:415:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:524:487:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:524:781:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:524:852:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:524:923:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:524:1228:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:524:1303:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:524:1378:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(input2.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:541:100:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Dispatch.h:31:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n", + " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n", + " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:541:344:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:541:416:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:541:488:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = double]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:541:782:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:541:853:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:541:924:\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 [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n", + "\u001b[01m\u001b[Kcorrelation_cuda_kernel.cu:541:1229:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:541:1304:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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[Kcorrelation_cuda_kernel.cu:541:1379:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[KT* at::Tensor::data() const [with T = c10::Half]\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n", + " AT_DISPATCH_FLOATING_TYPES_AND_HALF(rInput1.type(), \"lltm_forward_cuda\", ([&] {\n", + " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n", + "\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/core/TensorBody.h:322:1:\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_64-3.6\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 -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/correlation_cuda.o build/temp.linux-x86_64-3.6/correlation_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/correlation_cuda.cpython-36m-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_64-3.6/correlation_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n", + "creating stub loader for correlation_cuda.cpython-36m-x86_64-linux-gnu.so\n", + "byte-compiling build/bdist.linux-x86_64/egg/correlation_cuda.py to correlation_cuda.cpython-36.pyc\n", + "creating build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying correlation_cuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying correlation_cuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying correlation_cuda.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n", + "copying correlation_cuda.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__.correlation_cuda.cpython-36: module references __file__\n", + "creating dist\n", + "creating 'dist/correlation_cuda-0.0.0-py3.6-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 correlation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "creating /usr/local/lib/python3.6/dist-packages/correlation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Extracting correlation_cuda-0.0.0-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n", + "Adding correlation-cuda 0.0.0 to easy-install.pth file\n", + "\n", + "Installed /usr/local/lib/python3.6/dist-packages/correlation_cuda-0.0.0-py3.6-linux-x86_64.egg\n", + "Processing dependencies for correlation-cuda==0.0.0\n", + "Finished processing dependencies for correlation-cuda==0.0.0\n", + "Building #2 done.\n", + "/content/DAIN\n", + "--2020-03-22 00:34:18-- http://vllab1.ucmerced.edu/~wenbobao/DAIN/best.pth\n", + "Resolving vllab1.ucmerced.edu (vllab1.ucmerced.edu)... 169.236.184.68\n", + "Connecting to vllab1.ucmerced.edu (vllab1.ucmerced.edu)|169.236.184.68|:80... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 96319643 (92M)\n", + "Saving to: ‘model_weights/best.pth’\n", + "\n", + "model_weights/best. 100%[===================>] 91.86M 15.6MB/s in 7.1s \n", + "\n", + "2020-03-22 00:34:26 (13.0 MB/s) - ‘model_weights/best.pth’ saved [96319643/96319643]\n", + "\n", + "/content/DAIN/MiddleBurySet\n", + "--2020-03-22 00:34:28-- http://vision.middlebury.edu/flow/data/comp/zip/other-color-allframes.zip\n", + "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n", + "Connecting to vision.middlebury.edu (vision.middlebury.edu)|140.233.20.14|:80... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 33671986 (32M) [application/zip]\n", + "Saving to: ‘other-color-allframes.zip’\n", + "\n", + "other-color-allfram 100%[===================>] 32.11M 8.24MB/s in 3.9s \n", + "\n", + "2020-03-22 00:34:33 (8.24 MB/s) - 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scipy-1.0.0\n" ], "name": "stdout" }, { - "output_type": "error", - "ename": "MessageError", - "evalue": "ignored", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mMessageError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;31m# Building DAIN PyTorch correlation package.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'cd /content/DAIN/PWCNet/correlation_package_pytorch1_0'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m 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"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/google/colab/_system_commands.py\u001b[0m in \u001b[0;36m_run_command\u001b[0;34m(cmd, clear_streamed_output)\u001b[0m\n\u001b[1;32m 179\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 180\u001b[0m with temporary_clearer(), _display_stdin_widget(\n\u001b[0;32m--> 181\u001b[0;31m delay_millis=500) as update_stdin_widget:\n\u001b[0m\u001b[1;32m 182\u001b[0m \u001b[0;31m# TODO(b/115531839): Ensure that subprocesses are terminated upon\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 183\u001b[0m \u001b[0;31m# interrupt.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/lib/python3.6/contextlib.py\u001b[0m in \u001b[0;36m__enter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__enter__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 80\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 81\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 82\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 83\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"generator didn't yield\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/google/colab/_system_commands.py\u001b[0m in \u001b[0;36m_display_stdin_widget\u001b[0;34m(delay_millis)\u001b[0m\n\u001b[1;32m 339\u001b[0m \u001b[0mshell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_ipython\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 340\u001b[0m \u001b[0mdisplay_args\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'cell_display_stdin'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'delayMillis'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mdelay_millis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 341\u001b[0;31m \u001b[0m_message\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mblocking_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mdisplay_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshell\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparent_header\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 342\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 343\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mecho_updater\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_echo_status\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/google/colab/_message.py\u001b[0m in \u001b[0;36mblocking_request\u001b[0;34m(request_type, request, timeout_sec, parent)\u001b[0m\n\u001b[1;32m 169\u001b[0m \u001b[0;31m# unique.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 170\u001b[0m \u001b[0mrequest_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msend_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparent\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 171\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mread_reply_from_input\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout_sec\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/google/colab/_message.py\u001b[0m in \u001b[0;36mread_reply_from_input\u001b[0;34m(message_id, timeout_sec)\u001b[0m\n\u001b[1;32m 104\u001b[0m reply.get('colab_msg_id') == message_id):\n\u001b[1;32m 105\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m'error'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 106\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mMessageError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreply\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'error'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 107\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 108\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mMessageError\u001b[0m: Error: Cell has no view" - ] + "output_type": "display_data", + "data": { + "application/vnd.colab-display-data+json": { + "pip_warning": { + "packages": [ + "numpy" + ] + } + } + }, + "metadata": { + "tags": [] + } } ] }, @@ -231,7 +2629,7 @@ "metadata": { "id": "9YNva-GuKq4Y", "colab_type": "code", - "outputId": "081cb6d7-b383-4d1c-d87b-40c66504b439", + "outputId": "204218dd-8198-4c9f-a378-89fb343655d2", "colab": { "base_uri": "https://localhost:8080/", "height": 51 @@ -250,28 +2648,28 @@ "fps = cap.get(cv2.CAP_PROP_FPS)\n", "\n", "# ffmpeg extract - Generating individual frame PNGs from the source file.\n", - "%shell rm -rf /content/DAIN/input_frames\n", - "%shell mkdir -p /content/DAIN/input_frames\n", + "%shell rm -rf {FRAME_INPUT_DIR}\n", + "%shell mkdir -p {FRAME_INPUT_DIR}\n", "\n", "# TODO: Work with this to remove the alpha channel\n", - "#%shell ffmpeg -i '/content/DAIN/{filename}' -filter_complex 'split [rgb_in][alpha_in]; [rgb_in][out];' '/content/DAIN/input_frames/%05d.png'\n", + "#%shell ffmpeg -i '/content/DAIN/{filename}' -filter_complex 'split [rgb_in][alpha_in]; [rgb_in][out];' '{FRAME_INPUT_DIR}'\n", "\n", - "%shell ffmpeg -i '/content/DAIN/{filename}' '/content/DAIN/input_frames/%05d.png'\n", + "%shell ffmpeg -i '/content/DAIN/{filename}' '{FRAME_INPUT_DIR}/%05d.png'\n", "\n", - "png_generated_count_command_result = %shell ls /content/DAIN/input_frames | wc -l\n", + "png_generated_count_command_result = %shell ls {FRAME_INPUT_DIR} | wc -l\n", "clear_output()\n", "\n", "pngs_generated_count = int(png_generated_count_command_result.output.strip())\n", "print(f\"Input FPS: {fps}\")\n", "print(f\"{pngs_generated_count} frame PNGs generated.\")" ], - "execution_count": 61, + "execution_count": 20, "outputs": [ { "output_type": "stream", "text": [ - "Input FPS: 10.0\n", - "24 frame PNGs generated.\n" + "Input FPS: 11.11111111111111\n", + "11 frame PNGs generated.\n" ], "name": "stdout" } @@ -282,7 +2680,7 @@ "metadata": { "id": "W3rrE7L824gL", "colab_type": "code", - "outputId": "a56f3fd1-5f81-427f-af44-7e82471cf57f", + "outputId": "88b62aad-c6c3-4e45-ff4e-97f548ece8b0", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 @@ -290,22 +2688,21 @@ }, "source": [ "# Interpolation\n", - "%shell rm -rf /content/DAIN/output_frames\n", - "%shell mkdir /content/DAIN/output_frames\n", + "%shell mkdir -p {FRAME_OUTPUT_DIR}\n", "%cd /content/DAIN\n", - "#!python colab_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step {fps/TARGET_FPS} --save_which=0\n", - "!python colab_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step {fps/TARGET_FPS}" + "\n", + "!python colab_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step {fps/TARGET_FPS} --start_frame 1 --end_frame {pngs_generated_count} --frame_input_dir {FRAME_INPUT_DIR} --frame_output_dir {FRAME_OUTPUT_DIR}" ], - "execution_count": 64, + "execution_count": 21, "outputs": [ { "output_type": "stream", "text": [ "/content/DAIN\n", - "revise the unique id to a random numer 80195\n", - "Namespace(SAVED_MODEL=None, alpha=[0.0, 1.0], arg='./model_weights/80195-Mon-Mar-09-17:24/args.txt', batch_size=1, channels=3, ctx_lr_coe=1.0, datasetName='Vimeo_90K_interp', datasetPath='', dataset_split=97, debug=False, depth_lr_coe=0.001, dtype=, epsilon=1e-06, factor=0.2, filter_lr_coe=1.0, filter_size=4, flow_lr_coe=0.01, force=False, log='./model_weights/80195-Mon-Mar-09-17:24/log.txt', lr=0.002, netName='DAIN_slowmotion', no_date=False, numEpoch=100, occ_lr_coe=1.0, patience=5, rectify_lr=0.001, save_path='./model_weights/80195-Mon-Mar-09-17:24', save_which=1, seed=1, time_step=0.16666666666666666, uid=None, use_cuda=True, use_cudnn=1, weight_decay=0, workers=8)\n", + "revise the unique id to a random numer 32841\n", + "Namespace(SAVED_MODEL=None, alpha=[0.0, 1.0], arg='./model_weights/32841-Sun-Mar-22-01:38/args.txt', batch_size=1, channels=3, ctx_lr_coe=1.0, datasetName='Vimeo_90K_interp', datasetPath='', dataset_split=97, debug=False, depth_lr_coe=0.001, dtype=, end_frame=11, epsilon=1e-06, factor=0.2, filter_lr_coe=1.0, filter_size=4, flow_lr_coe=0.01, force=False, frame_input_dir='/content/DAIN/input_frames', frame_output_dir='/content/DAIN/output_frames', log='./model_weights/32841-Sun-Mar-22-01:38/log.txt', lr=0.002, netName='DAIN_slowmotion', no_date=False, numEpoch=100, occ_lr_coe=1.0, patience=5, rectify_lr=0.001, save_path='./model_weights/32841-Sun-Mar-22-01:38', save_which=1, seed=1, start_frame=1, time_step=0.18518518518518517, uid=None, use_cuda=True, use_cudnn=1, weight_decay=0, workers=8)\n", "cudnn is used\n", - "Interpolate 5 frames\n", + "Interpolate 4 frames\n", "The testing model weight is: ./model_weights/best.pth\n", "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2506: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.\n", " \"See the documentation of nn.Upsample for details.\".format(mode))\n", @@ -332,32 +2729,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 2 | Time per image (avg): 18.37s | Time left: 0:30:00.748411 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 3 | Time per image (avg): 11.83s | Time left: 0:19:07.533339 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 4 | Time per image (avg): 9.65s | Time left: 0:15:26.129295 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 2 | Time per image (avg): 11.63s | Time left: 0:01:44.663959 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -365,10 +2737,10 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 5 | Time per image (avg): 8.56s | Time left: 0:13:32.894993 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 3 | Time per image (avg): 6.85s | Time left: 0:00:54.765493 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -376,10 +2748,10 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 6 | Time per image (avg): 7.90s | Time left: 0:12:22.980276 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 4 | Time per image (avg): 5.26s | Time left: 0:00:36.823278 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -387,10 +2759,10 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 7 | Time per image (avg): 7.47s | Time left: 0:11:34.856824 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 5 | Time per image (avg): 4.47s | Time left: 0:00:26.809363 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -398,10 +2770,10 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 8 | Time per image (avg): 7.16s | Time left: 0:10:58.896966 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 6 | Time per image (avg): 3.99s | Time left: 0:00:19.969475 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -409,10 +2781,10 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 9 | Time per image (avg): 6.93s | Time left: 0:10:30.423218 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 7 | Time per image (avg): 3.68s | Time left: 0:00:14.700462 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -420,10 +2792,10 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 10 | Time per image (avg): 6.74s | Time left: 0:10:07.001162 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 8 | Time per image (avg): 3.45s | Time left: 0:00:10.342627 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -431,10 +2803,10 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 11 | Time per image (avg): 6.60s | Time left: 0:09:47.278288 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", + "******Processed image 9 | Time per image (avg): 3.28s | Time left: 0:00:06.561957 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -442,138 +2814,11 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 12 | Time per image (avg): 6.48s | Time left: 0:09:30.144293 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 13 | Time per image (avg): 6.38s | Time left: 0:09:15.017867 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 14 | Time per image (avg): 6.29s | Time left: 0:09:01.348236 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 15 | Time per image (avg): 6.22s | Time left: 0:08:48.927728 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 16 | Time per image (avg): 6.16s | Time left: 0:08:37.536027 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 17 | Time per image (avg): 6.11s | Time left: 0:08:26.920908 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 18 | Time per image (avg): 6.06s | Time left: 0:08:16.881724 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 19 | Time per image (avg): 6.02s | Time left: 0:08:07.430273 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 20 | Time per image (avg): 5.98s | Time left: 0:07:58.342936 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 21 | Time per image (avg): 5.95s | Time left: 0:07:49.670338 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 22 | Time per image (avg): 5.91s | Time left: 0:07:41.278807 ******************\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 23 | Time per image (avg): 5.89s | Time left: 0:07:33.230222 ******************\n", - "Traceback (most recent call last):\n", - " File \"test.py\", line 91, in \n", - " X1 = torch.from_numpy( np.transpose(imread(arguments_strSecond), (2,0,1)).astype(\"float32\")/ 255.0).type(dtype)\n", - " File \"/usr/local/lib/python3.6/dist-packages/numpy/lib/utils.py\", line 101, in newfunc\n", - " return func(*args, **kwds)\n", - " File \"/usr/local/lib/python3.6/dist-packages/scipy/misc/pilutil.py\", line 164, in imread\n", - " im = Image.open(name)\n", - " File \"/usr/local/lib/python3.6/dist-packages/PIL/Image.py\", line 2766, in open\n", - " fp = builtins.open(filename, \"rb\")\n", - "FileNotFoundError: [Errno 2] No such file or directory: '/content/DAIN/input_frames/00025.png'\n" + "******Processed image 10 | Time per image (avg): 3.15s | Time left: 0:00:03.153109 ******************\n", + "Finished processing images.\n" ], "name": "stdout" } @@ -584,16 +2829,16 @@ "metadata": { "id": "TKREDli2IDMV", "colab_type": "code", - "outputId": "8c3c012a-d9f0-4071-8567-c3408bb45272", + "outputId": "f12bb8db-b071-463f-c2fa-a5ec7cd7c133", "colab": { "base_uri": "https://localhost:8080/", - "height": 836 + "height": 819 } }, "source": [ - "%shell ffmpeg -y -r {TARGET_FPS} -f image2 -i '/content/DAIN/output_frames/%05d.png' output.mkv" + "%shell ffmpeg -y -r {TARGET_FPS} -f image2 -i '{FRAME_OUTPUT_DIR}/%05d.png' '/content/gdrive/My Drive/{OUTPUT_FILE_PATH}'" ], - "execution_count": 65, + "execution_count": 24, "outputs": [ { "output_type": "stream", @@ -611,40 +2856,39 @@ " libswresample 2. 9.100 / 2. 9.100\n", " libpostproc 54. 7.100 / 54. 7.100\n", "Input #0, image2, from '/content/DAIN/output_frames/%05d.png':\n", - " Duration: 00:00:02.30, start: 0.000000, bitrate: N/A\n", - " Stream #0:0: Video: png, rgb24(pc), 722x928 [SAR 1:1 DAR 361:464], 60 fps, 60 tbr, 60 tbn, 60 tbc\n", + " Duration: 00:00:00.83, start: 0.000000, bitrate: N/A\n", + " Stream #0:0: Video: png, rgb24(pc), 480x330, 60 fps, 60 tbr, 60 tbn, 60 tbc\n", "Stream mapping:\n", " Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n", "Press [q] to stop, [?] for help\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0musing SAR=1/1\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0musing cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mprofile High 4:4:4 Predictive, level 3.2, 4:4:4 8-bit\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0m264 - core 152 r2854 e9a5903 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x1:0x111 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=4 threads=3 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n", - "Output #0, matroska, to 'output.mkv':\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0musing cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mprofile High 4:4:4 Predictive, level 3.0, 4:4:4 8-bit\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0m264 - core 152 r2854 e9a5903 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x1:0x111 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=4 threads=3 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n", + "Output #0, mp4, to '/content/gdrive/My Drive/DAIN/batmanOut.mp4':\n", " Metadata:\n", " encoder : Lavf57.83.100\n", - " Stream #0:0: Video: h264 (libx264) (H264 / 0x34363248), yuv444p, 722x928 [SAR 1:1 DAR 361:464], q=-1--1, 60 fps, 1k tbn, 60 tbc\n", + " Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv444p, 480x330, q=-1--1, 60 fps, 15360 tbn, 60 tbc\n", " Metadata:\n", " encoder : Lavc57.107.100 libx264\n", " Side data:\n", " cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1\n", - "frame= 138 fps= 30 q=-1.0 Lsize= 343kB time=00:00:02.25 bitrate=1247.8kbits/s speed=0.482x \n", - "video:341kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.500059%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mframe I:1 Avg QP:22.86 size: 21701\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mframe P:35 Avg QP:25.58 size: 5529\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mframe B:102 Avg QP:31.20 size: 1309\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mconsecutive B-frames: 1.4% 0.0% 0.0% 98.6%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mmb I I16..4: 59.2% 0.0% 40.8%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mmb P I16..4: 3.7% 0.0% 0.9% P16..4: 31.1% 10.3% 3.9% 0.0% 0.0% skip:50.0%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mmb B I16..4: 0.1% 0.0% 0.0% B16..8: 28.6% 2.2% 0.2% direct: 0.2% skip:68.7% L0:45.4% L1:50.4% BI: 4.3%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mcoded y,u,v intra: 19.9% 4.1% 7.3% inter: 1.9% 0.0% 0.2%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mi16 v,h,dc,p: 40% 32% 12% 15%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 26% 25% 22% 4% 5% 5% 6% 4% 3%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mWeighted P-Frames: Y:0.0% UV:0.0%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mref P L0: 56.6% 10.5% 24.3% 8.7%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mref B L0: 85.5% 8.6% 5.9%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mref B L1: 95.5% 4.5%\n", - "\u001b[1;36m[libx264 @ 0x55f3ba591e00] \u001b[0mkb/s:1212.77\n" + "frame= 50 fps=0.0 q=-1.0 Lsize= 26kB time=00:00:00.78 bitrate= 268.9kbits/s speed=1.31x \n", + "video:24kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 5.758805%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mframe I:1 Avg QP:24.34 size: 6426\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mframe P:13 Avg QP:26.56 size: 761\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mframe B:36 Avg QP:29.48 size: 219\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mconsecutive B-frames: 4.0% 0.0% 0.0% 96.0%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mmb I I16..4: 45.4% 0.0% 54.6%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mmb P I16..4: 0.6% 0.0% 0.7% P16..4: 31.1% 5.4% 3.8% 0.0% 0.0% skip:58.5%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mmb B I16..4: 0.0% 0.0% 0.0% B16..8: 27.4% 0.7% 0.1% direct: 0.1% skip:71.7% L0:41.2% L1:58.1% BI: 0.6%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mcoded y,u,v intra: 44.1% 17.3% 9.4% inter: 1.0% 0.3% 0.0%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mi16 v,h,dc,p: 29% 32% 24% 15%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 27% 13% 26% 5% 6% 4% 7% 8% 6%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mWeighted P-Frames: Y:0.0% UV:0.0%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mref P L0: 60.7% 8.8% 21.3% 9.2%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mref B L0: 81.5% 12.6% 5.9%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mref B L1: 93.8% 6.2%\n", + "\u001b[1;36m[libx264 @ 0x5652dbe13e00] \u001b[0mkb/s:232.44\n" ], "name": "stdout" }, @@ -658,23 +2902,9 @@ "metadata": { "tags": [] }, - "execution_count": 65 + "execution_count": 24 } ] - }, - { - "cell_type": "code", - "metadata": { - "id": "ugAre_7dJ8YJ", - "colab_type": "code", - "colab": {} - }, - "source": [ - "# Copy result to drive\n", - "!cp /content/DAIN/output.mkv '/content/gdrive/My Drive/{OUTPUT_FILE_PATH}'" - ], - "execution_count": 0, - "outputs": [] } ] -} +} \ No newline at end of file diff --git a/colab_MiddleBury_slowmotion.py b/colab_MiddleBury_slowmotion.py index c0ec5ef..161cc4f 100644 --- a/colab_MiddleBury_slowmotion.py +++ b/colab_MiddleBury_slowmotion.py @@ -5,7 +5,7 @@ import numpy as np import numpy import networks -from my_args import args +from my_args import args from scipy.misc import imread, imsave from AverageMeter import * import shutil @@ -52,20 +52,22 @@ save_which = args.save_which dtype = args.dtype -frames_dir = '/content/DAIN/input_frames' -output_dir = '/content/DAIN/output_frames' +frames_dir = args.frame_input_dir +output_dir = args.frame_output_dir timestep = args.time_step time_offsets = [kk * timestep for kk in range(1, int(1.0 / timestep))] output_frame_count = 1 -input_frame = 0 +input_frame = args.start_frame - 1 loop_timer = AverageMeter() -# TODO: Read amount of frames from the size of files available in `frames_dir` -final_frame = 100 +final_frame = args.end_frame -while input_frame < final_frame: +# we want to have input_frame between (start_frame-1) and (end_frame-2) +# this is because at each step we read (frame) and (frame+1) +# so the last iteration will actuall be (end_frame-1) and (end_frame) +while input_frame < final_frame - 1: input_frame += 1 start_time = time.time() diff --git a/my_args.py b/my_args.py index ad3b5e0..ac41097 100644 --- a/my_args.py +++ b/my_args.py @@ -66,6 +66,12 @@ parser.add_argument('--uid', type=str, default= None, help='unique id for the training') parser.add_argument('--force', action='store_true', help='force to override the given uid') +# Colab version +parser.add_argument('--start_frame', type = int, default = 1, help='first frame number to process') +parser.add_argument('--end_frame', type = int, default = 100, help='last frame number to process') +parser.add_argument('--frame_input_dir', type = str, default = '/content/DAIN/input_frames', help='frame input directory') +parser.add_argument('--frame_output_dir', type = str, default = '/content/DAIN/output_frames', help='frame output directory') + args = parser.parse_args() import shutil From be1e172172cb50484239ee809f947b3848b8001d Mon Sep 17 00:00:00 2001 From: Alpha Date: Sat, 21 Mar 2020 22:01:50 -0400 Subject: [PATCH 2/8] Preserving spaces in directory paths when calling commands --- Colab_DAIN_alpha.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/Colab_DAIN_alpha.ipynb b/Colab_DAIN_alpha.ipynb index 29823cd..8d86bbf 100644 --- a/Colab_DAIN_alpha.ipynb +++ b/Colab_DAIN_alpha.ipynb @@ -2648,15 +2648,15 @@ "fps = cap.get(cv2.CAP_PROP_FPS)\n", "\n", "# ffmpeg extract - Generating individual frame PNGs from the source file.\n", - "%shell rm -rf {FRAME_INPUT_DIR}\n", - "%shell mkdir -p {FRAME_INPUT_DIR}\n", + "%shell rm -rf '{FRAME_INPUT_DIR}'\n", + "%shell mkdir -p '{FRAME_INPUT_DIR}'\n", "\n", "# TODO: Work with this to remove the alpha channel\n", "#%shell ffmpeg -i '/content/DAIN/{filename}' -filter_complex 'split [rgb_in][alpha_in]; [rgb_in][out];' '{FRAME_INPUT_DIR}'\n", "\n", "%shell ffmpeg -i '/content/DAIN/{filename}' '{FRAME_INPUT_DIR}/%05d.png'\n", "\n", - "png_generated_count_command_result = %shell ls {FRAME_INPUT_DIR} | wc -l\n", + "png_generated_count_command_result = %shell ls '{FRAME_INPUT_DIR}' | wc -l\n", "clear_output()\n", "\n", "pngs_generated_count = int(png_generated_count_command_result.output.strip())\n", @@ -2688,10 +2688,10 @@ }, "source": [ "# Interpolation\n", - "%shell mkdir -p {FRAME_OUTPUT_DIR}\n", + "%shell mkdir -p '{FRAME_OUTPUT_DIR}'\n", "%cd /content/DAIN\n", "\n", - "!python colab_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step {fps/TARGET_FPS} --start_frame 1 --end_frame {pngs_generated_count} --frame_input_dir {FRAME_INPUT_DIR} --frame_output_dir {FRAME_OUTPUT_DIR}" + "!python colab_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step {fps/TARGET_FPS} --start_frame 1 --end_frame {pngs_generated_count} --frame_input_dir '{FRAME_INPUT_DIR}' --frame_output_dir '{FRAME_OUTPUT_DIR}'" ], "execution_count": 21, "outputs": [ From 153e42646c4441536a5821e95d49b81ea57a0a0a Mon Sep 17 00:00:00 2001 From: Alpha Date: Sat, 21 Mar 2020 22:27:29 -0400 Subject: [PATCH 3/8] Improve loop measurement --- colab_MiddleBury_slowmotion.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/colab_MiddleBury_slowmotion.py b/colab_MiddleBury_slowmotion.py index 161cc4f..06cc203 100644 --- a/colab_MiddleBury_slowmotion.py +++ b/colab_MiddleBury_slowmotion.py @@ -129,11 +129,6 @@ y_s,offset,filter = model(torch.stack((X0, X1),dim = 0)) y_ = y_s[save_which] - frames_left = final_frame - input_frame - estimated_seconds_left = frames_left * loop_timer.avg - estimated_time_left = datetime.timedelta(seconds=estimated_seconds_left) - print(f"******Processed image {input_frame} | Time per image (avg): {loop_timer.avg:2.2f}s | Time left: {estimated_time_left} ******************" ) - if use_cuda: X0 = X0.data.cpu().numpy() if not isinstance(y_, list): @@ -172,4 +167,9 @@ end_time = time.time() loop_timer.update(end_time - start_time) + frames_left = final_frame - input_frame + estimated_seconds_left = frames_left * loop_timer.avg + estimated_time_left = datetime.timedelta(seconds=estimated_seconds_left) + print(f"****** Processed frame {input_frame} | Time per frame (avg): {loop_timer.avg:2.2f}s | Time left: {estimated_time_left} ******************" ) + print("Finished processing images.") From c2d7e6c402568efeae731a999bad928c68713050 Mon Sep 17 00:00:00 2001 From: Alpha Date: Sat, 21 Mar 2020 23:02:42 -0400 Subject: [PATCH 4/8] Keeping deterministic file naming on arbitrary start --- Colab_DAIN_alpha.ipynb | 11 ++++++++--- colab_MiddleBury_slowmotion.py | 14 ++++++++------ 2 files changed, 16 insertions(+), 9 deletions(-) diff --git a/Colab_DAIN_alpha.ipynb b/Colab_DAIN_alpha.ipynb index 8d86bbf..add6fef 100644 --- a/Colab_DAIN_alpha.ipynb +++ b/Colab_DAIN_alpha.ipynb @@ -50,7 +50,8 @@ "- Gif (RGBA24 or alpha in general) is currently not supported.\n", "- Adding configuration to select speed.\n", "- Detect scenes to avoid interpolating scene-changes\n", - "- Auto-resume" + "- Auto-resume\n", + "- Copy `start_frame` - `end_frame` audio from original input to final output" ] }, { @@ -61,7 +62,8 @@ "colab": {} }, "source": [ - "################# Configuration cell! ############################\n", + "################# Configurations ############################\n", + "\n", "# Use the values in here to configure what you'd like DAIN to do.\n", "\n", "# Input file: Path (relative to the root of your Google Drive) to the input file.\n", @@ -73,6 +75,8 @@ "# Extension should always be MP4.\n", "OUTPUT_FILE_PATH = \"DAIN/batmanOut.mp4\"\n", "\n", + "################# Optional configurations ############################\n", + "\n", "# Target FPS = how many frames per second should the result have. This will determine how many intermediate images are\n", "# interpolated.\n", "TARGET_FPS = 60\n", @@ -2836,7 +2840,8 @@ } }, "source": [ - "%shell ffmpeg -y -r {TARGET_FPS} -f image2 -i '{FRAME_OUTPUT_DIR}/%05d.png' '/content/gdrive/My Drive/{OUTPUT_FILE_PATH}'" + "%cd {FRAME_OUTPUT_DIR}\n", + "%shell ffmpeg -y -r {TARGET_FPS} -f image2 -pattern_type glob -i '*.png' '/content/gdrive/My Drive/{OUTPUT_FILE_PATH}'" ], "execution_count": 24, "outputs": [ diff --git a/colab_MiddleBury_slowmotion.py b/colab_MiddleBury_slowmotion.py index 06cc203..243f3bf 100644 --- a/colab_MiddleBury_slowmotion.py +++ b/colab_MiddleBury_slowmotion.py @@ -58,7 +58,6 @@ timestep = args.time_step time_offsets = [kk * timestep for kk in range(1, int(1.0 / timestep))] -output_frame_count = 1 input_frame = args.start_frame - 1 loop_timer = AverageMeter() @@ -80,7 +79,6 @@ arguments_strFirst = os.path.join(frames_dir, str(dateiname_start)+'.png') #frame10.png arguments_strSecond = os.path.join(frames_dir, str(dateiname_ende)+'.png') #frame11 - X0 = torch.from_numpy( np.transpose(imread(arguments_strFirst), (2,0,1)).astype("float32")/ 255.0).type(dtype) X1 = torch.from_numpy( np.transpose(imread(arguments_strSecond), (2,0,1)).astype("float32")/ 255.0).type(dtype) @@ -157,12 +155,12 @@ (1, 2, 0)) for filter_i in filter] if filter is not None else None X1 = np.transpose(255.0 * X1.clip(0,1.0)[0, :, intPaddingTop:intPaddingTop+intHeight, intPaddingLeft: intPaddingLeft+intWidth], (1, 2, 0)) - shutil.copy(arguments_strFirst, os.path.join(output_dir, f"{output_frame_count:0>5d}.png")) - output_frame_count += 1 + interpolated_frame_number = 0 + shutil.copy(arguments_strFirst, os.path.join(output_dir, f"{input_frame:0>5d}{interpolated_frame_number:0>3d}.png")) for item, time_offset in zip(y_, time_offsets): - output_frame_file_path = os.path.join(output_dir, f"{output_frame_count:0>5d}.png") + interpolated_frame_number += 1 + output_frame_file_path = os.path.join(output_dir, f"{input_frame:0>5d}{interpolated_frame_number:0>3d}.png") imsave(output_frame_file_path, np.round(item).astype(numpy.uint8)) - output_frame_count += 1 end_time = time.time() loop_timer.update(end_time - start_time) @@ -172,4 +170,8 @@ estimated_time_left = datetime.timedelta(seconds=estimated_seconds_left) print(f"****** Processed frame {input_frame} | Time per frame (avg): {loop_timer.avg:2.2f}s | Time left: {estimated_time_left} ******************" ) +# Copying last frame +last_frame_filename = os.path.join(frames_dir, str(str(final_frame).zfill(5))+'.png') +shutil.copy(last_frame_filename, os.path.join(output_dir, f"{final_frame:0>5d}{0:0>3d}.png")) + print("Finished processing images.") From cc9a6b5bd59ad3c27f9b6431fc060c9815745409 Mon Sep 17 00:00:00 2001 From: Alpha Date: Sun, 22 Mar 2020 16:40:38 -0400 Subject: [PATCH 5/8] Removed unused code, improved performance, adapted to SciPy 1.2 --- ...Bury_slowmotion.py => colab_interpolate.py | 87 ++++++++----------- 1 file changed, 36 insertions(+), 51 deletions(-) rename colab_MiddleBury_slowmotion.py => colab_interpolate.py (66%) diff --git a/colab_MiddleBury_slowmotion.py b/colab_interpolate.py similarity index 66% rename from colab_MiddleBury_slowmotion.py rename to colab_interpolate.py index 243f3bf..9922d96 100644 --- a/colab_MiddleBury_slowmotion.py +++ b/colab_interpolate.py @@ -6,51 +6,44 @@ import numpy import networks from my_args import args -from scipy.misc import imread, imsave +from imageio import imread, imsave from AverageMeter import * import shutil import datetime torch.backends.cudnn.benchmark = True model = networks.__dict__[args.netName]( - channel=args.channels, + channel = args.channels, filter_size = args.filter_size, - timestep=args.time_step, - training=False) + timestep = args.time_step, + training = False) if args.use_cuda: model = model.cuda() -args.SAVED_MODEL = './model_weights/best.pth' -if os.path.exists(args.SAVED_MODEL): - print("The testing model weight is: " + args.SAVED_MODEL) - if not args.use_cuda: - pretrained_dict = torch.load(args.SAVED_MODEL, map_location=lambda storage, loc: storage) - # model.load_state_dict(torch.load(args.SAVED_MODEL, map_location=lambda storage, loc: storage)) - else: - pretrained_dict = torch.load(args.SAVED_MODEL) - # model.load_state_dict(torch.load(args.SAVED_MODEL)) - - model_dict = model.state_dict() - # 1. filter out unnecessary keys - pretrained_dict = {k: v for k, v in pretrained_dict.items() if k in model_dict} - # 2. overwrite entries in the existing state dict - model_dict.update(pretrained_dict) - # 3. load the new state dict - model.load_state_dict(model_dict) - # 4. release the pretrained dict for saving memory - pretrained_dict = [] -else: +model_path = './model_weights/best.pth' +if not os.path.exists(model_path): print("*****************************************************************") print("**** We couldn't load any trained weights ***********************") print("*****************************************************************") exit(1) -model = model.eval() # deploy mode +if args.use_cuda: + pretrained_dict = torch.load(model_path) +else: + pretrained_dict = torch.load(model_path, map_location=lambda storage, loc: storage) + +model_dict = model.state_dict() +# 1. filter out unnecessary keys +pretrained_dict = {k: v for k, v in pretrained_dict.items() if k in model_dict} +# 2. overwrite entries in the existing state dict +model_dict.update(pretrained_dict) +# 3. load the new state dict +model.load_state_dict(model_dict) +# 4. release the pretrained dict for saving memory +pretrained_dict = [] -use_cuda = args.use_cuda -save_which = args.save_which -dtype = args.dtype +model = model.eval() # deploy mode frames_dir = args.frame_input_dir output_dir = args.frame_output_dir @@ -63,6 +56,8 @@ final_frame = args.end_frame +torch.set_grad_enabled(False) + # we want to have input_frame between (start_frame-1) and (end_frame-2) # this is because at each step we read (frame) and (frame+1) # so the last iteration will actuall be (end_frame-1) and (end_frame) @@ -71,35 +66,27 @@ start_time = time.time() - #input file names - dateiname_start = input_frame - dateiname_start = str(dateiname_start).zfill(5) - dateiname_ende = input_frame + 1 - dateiname_ende = str(dateiname_ende).zfill(5) - arguments_strFirst = os.path.join(frames_dir, str(dateiname_start)+'.png') #frame10.png - arguments_strSecond = os.path.join(frames_dir, str(dateiname_ende)+'.png') #frame11 - - X0 = torch.from_numpy( np.transpose(imread(arguments_strFirst), (2,0,1)).astype("float32")/ 255.0).type(dtype) - X1 = torch.from_numpy( np.transpose(imread(arguments_strSecond), (2,0,1)).astype("float32")/ 255.0).type(dtype) + filename_frame_1 = os.path.join(frames_dir, f'{input_frame:0>5d}.png') + filename_frame_2 = os.path.join(frames_dir, f'{input_frame+1:0>5d}.png') - y_ = torch.FloatTensor() + X0 = torch.from_numpy(np.transpose(imread(filename_frame_1), (2,0,1)).astype("float32") / 255.0).type(args.dtype) + X1 = torch.from_numpy(np.transpose(imread(filename_frame_2), (2,0,1)).astype("float32") / 255.0).type(args.dtype) assert (X0.size(1) == X1.size(1)) assert (X0.size(2) == X1.size(2)) intWidth = X0.size(2) intHeight = X0.size(1) - channel = X0.size(0) - if not channel == 3: - print(f"Skipping {frame_1_filename}-{frame_2_filename} -- expected 3 color channels but found {channel}.") + channels = X0.size(0) + if not channels == 3: + print(f"Skipping {filename_frame_1}-{filename_frame_2} -- expected 3 color channels but found {channels}.") continue if intWidth != ((intWidth >> 7) << 7): intWidth_pad = (((intWidth >> 7) + 1) << 7) # more than necessary - intPaddingLeft =int(( intWidth_pad - intWidth)/2) + intPaddingLeft = int((intWidth_pad - intWidth) / 2) intPaddingRight = intWidth_pad - intWidth - intPaddingLeft else: - intWidth_pad = intWidth intPaddingLeft = 32 intPaddingRight= 32 @@ -108,26 +95,24 @@ intPaddingTop = int((intHeight_pad - intHeight) / 2) intPaddingBottom = intHeight_pad - intHeight - intPaddingTop else: - intHeight_pad = intHeight intPaddingTop = 32 intPaddingBottom = 32 pader = torch.nn.ReplicationPad2d([intPaddingLeft, intPaddingRight, intPaddingTop, intPaddingBottom]) - torch.set_grad_enabled(False) X0 = Variable(torch.unsqueeze(X0,0)) X1 = Variable(torch.unsqueeze(X1,0)) X0 = pader(X0) X1 = pader(X1) - if use_cuda: + if args.use_cuda: X0 = X0.cuda() X1 = X1.cuda() - y_s,offset,filter = model(torch.stack((X0, X1),dim = 0)) - y_ = y_s[save_which] + y_s, offset, filter = model(torch.stack((X0, X1),dim = 0)) + y_ = y_s[args.save_which] - if use_cuda: + if args.use_cuda: X0 = X0.data.cpu().numpy() if not isinstance(y_, list): y_ = y_.data.cpu().numpy() @@ -156,7 +141,7 @@ X1 = np.transpose(255.0 * X1.clip(0,1.0)[0, :, intPaddingTop:intPaddingTop+intHeight, intPaddingLeft: intPaddingLeft+intWidth], (1, 2, 0)) interpolated_frame_number = 0 - shutil.copy(arguments_strFirst, os.path.join(output_dir, f"{input_frame:0>5d}{interpolated_frame_number:0>3d}.png")) + shutil.copy(filename_frame_1, os.path.join(output_dir, f"{input_frame:0>5d}{interpolated_frame_number:0>3d}.png")) for item, time_offset in zip(y_, time_offsets): interpolated_frame_number += 1 output_frame_file_path = os.path.join(output_dir, f"{input_frame:0>5d}{interpolated_frame_number:0>3d}.png") From 0e69259266f65e57de43c43838b34a1a835381d4 Mon Sep 17 00:00:00 2001 From: Alpha Date: Sun, 22 Mar 2020 16:45:21 -0400 Subject: [PATCH 6/8] Updated notebook --- Colab_DAIN_alpha.ipynb | 228 +++++------------------------------------ 1 file changed, 23 insertions(+), 205 deletions(-) diff --git a/Colab_DAIN_alpha.ipynb b/Colab_DAIN_alpha.ipynb index add6fef..1c0cc4b 100644 --- a/Colab_DAIN_alpha.ipynb +++ b/Colab_DAIN_alpha.ipynb @@ -72,7 +72,6 @@ "INPUT_FILEPATH = \"DAIN/batmanIn.mp4\"\n", "\n", "# Output file path: path (relative to the root of your Google Drive) for the output file.\n", - "# Extension should always be MP4.\n", "OUTPUT_FILE_PATH = \"DAIN/batmanOut.mp4\"\n", "\n", "################# Optional configurations ############################\n", @@ -117,11 +116,7 @@ { "output_type": "stream", "text": [ - "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n", - "\n", - "Enter your authorization code:\n", - "··········\n", - "Mounted at /content/gdrive\n", + "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n", "Google Drive connected.\n" ], "name": "stdout" @@ -170,9 +165,7 @@ "source": [ "# Install dependencies.\n", "\n", - "This next step may take somewhere between 15-20 minutes.\n", - "\n", - "Look for the \"Restart\" warning when it finishes, but **do not restart** the notebook.\n" + "This next step may take somewhere between 15-20 minutes.\n" ] }, { @@ -188,42 +181,26 @@ }, "source": [ "from IPython.display import clear_output\n", - "!rm -rf /content/DAIN\n", "!git clone https://github.com/styler00dollar/Colab-DAIN /content/DAIN\n", "\n", "# This takes a while. Just wait. ~15 minutes.\n", "# Building DAIN.\n", "%cd /content/DAIN/my_package/\n", "!./build.sh\n", - "#clear_output()\n", "print(\"Building #1 done.\")\n", "\n", "# Wait again. ~5 minutes.\n", "# Building DAIN PyTorch correlation package.\n", "%cd /content/DAIN/PWCNet/correlation_package_pytorch1_0\n", "!./build.sh\n", - "#clear_output()\n", "print(\"Building #2 done.\")\n", "\n", - "# Downloading pre-trained models\n", + "# Downloading pre-trained model\n", "%cd /content/DAIN\n", - "!mkdir model_weights MiddleBurySet\n", + "!mkdir model_weights\n", "!wget -O model_weights/best.pth http://vllab1.ucmerced.edu/~wenbobao/DAIN/best.pth\n", "\n", - "%cd /content/DAIN/MiddleBurySet\n", - "!wget http://vision.middlebury.edu/flow/data/comp/zip/other-color-allframes.zip\n", - "!unzip other-color-allframes.zip\n", - "\n", - "!wget http://vision.middlebury.edu/flow/data/comp/zip/other-gt-interp.zip\n", - "!unzip other-gt-interp.zip\n", - "#clear_output()\n", - "\n", - "!CUDA_VISIBLE_DEVICES=0\n", - "\n", - "# Fix scipy\n", - "# DO NOT RESTART YOUR COLAB!! Yes, there is red text and a warning, but it works.\n", - "\n", - "!pip install --force-reinstall scipy==1.0.0" + "!CUDA_VISIBLE_DEVICES=0" ], "execution_count": 5, "outputs": [ @@ -2461,170 +2438,12 @@ "Length: 96319643 (92M)\n", "Saving to: ‘model_weights/best.pth’\n", "\n", - "model_weights/best. 100%[===================>] 91.86M 15.6MB/s in 7.1s \n", - "\n", - "2020-03-22 00:34:26 (13.0 MB/s) - ‘model_weights/best.pth’ saved [96319643/96319643]\n", + "model_weights/best. 100%[===================>] 91.86M 18.7MB/s in 5.8s \n", "\n", - "/content/DAIN/MiddleBurySet\n", - "--2020-03-22 00:34:28-- http://vision.middlebury.edu/flow/data/comp/zip/other-color-allframes.zip\n", - "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n", - "Connecting to vision.middlebury.edu (vision.middlebury.edu)|140.233.20.14|:80... connected.\n", - "HTTP request sent, awaiting response... 200 OK\n", - "Length: 33671986 (32M) [application/zip]\n", - "Saving to: ‘other-color-allframes.zip’\n", - 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"\u001b[K |████████████████████████████████| 50.0MB 62kB/s \n", - "\u001b[?25hCollecting numpy>=1.8.2\n", - "\u001b[?25l Downloading https://files.pythonhosted.org/packages/07/08/a549ba8b061005bb629b76adc000f3caaaf881028b963c2e18f811c6edc1/numpy-1.18.2-cp36-cp36m-manylinux1_x86_64.whl (20.2MB)\n", - "\u001b[K |████████████████████████████████| 20.2MB 161kB/s \n", - "\u001b[31mERROR: tensorflow-model-optimization 0.2.1 requires enum34~=1.1, which is not installed.\u001b[0m\n", - "\u001b[31mERROR: tensorflow-federated 0.12.0 has requirement tensorflow~=2.1.0, but you'll have tensorflow 1.15.0 which is incompatible.\u001b[0m\n", - "\u001b[31mERROR: tensorflow-federated 0.12.0 has requirement tensorflow-addons~=0.7.0, but you'll have tensorflow-addons 0.8.3 which is incompatible.\u001b[0m\n", - "\u001b[31mERROR: seaborn 0.10.0 has requirement scipy>=1.0.1, but you'll have scipy 1.0.0 which is incompatible.\u001b[0m\n", - "\u001b[31mERROR: plotnine 0.6.0 has requirement scipy>=1.2.0, but you'll have scipy 1.0.0 which is incompatible.\u001b[0m\n", - "\u001b[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\u001b[0m\n", - "\u001b[31mERROR: cvxpy 1.0.28 has requirement scipy>=1.1.0, but you'll have scipy 1.0.0 which is incompatible.\u001b[0m\n", - "\u001b[31mERROR: albumentations 0.1.12 has requirement imgaug<0.2.7,>=0.2.5, but you'll have imgaug 0.2.9 which is incompatible.\u001b[0m\n", - "\u001b[?25hInstalling collected packages: numpy, scipy\n", - " Found existing installation: numpy 1.18.2\n", - " Uninstalling numpy-1.18.2:\n", - " Successfully uninstalled numpy-1.18.2\n", - " Found existing installation: scipy 1.4.1\n", - " Uninstalling scipy-1.4.1:\n", - " Successfully uninstalled scipy-1.4.1\n", - "Successfully installed numpy-1.18.2 scipy-1.0.0\n" + "2020-03-22 20:16:20 (15.7 MB/s) - ‘model_weights/best.pth’ saved [96319643/96319643]\n", + "\n" ], "name": "stdout" - }, - { - "output_type": "display_data", - "data": { - "application/vnd.colab-display-data+json": { - "pip_warning": { - "packages": [ - "numpy" - ] - } - } - }, - "metadata": { - "tags": [] - } } ] }, @@ -2633,11 +2452,11 @@ "metadata": { "id": "9YNva-GuKq4Y", "colab_type": "code", - "outputId": "204218dd-8198-4c9f-a378-89fb343655d2", "colab": { "base_uri": "https://localhost:8080/", "height": 51 - } + }, + "outputId": "ff983b7f-46e3-40f6-a549-2f501d320fc0" }, "source": [ "# Detecting FPS of input file.\n", @@ -2695,7 +2514,7 @@ "%shell mkdir -p '{FRAME_OUTPUT_DIR}'\n", "%cd /content/DAIN\n", "\n", - "!python colab_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step {fps/TARGET_FPS} --start_frame 1 --end_frame {pngs_generated_count} --frame_input_dir '{FRAME_INPUT_DIR}' --frame_output_dir '{FRAME_OUTPUT_DIR}'" + "!python colab_interpolate.py --netName DAIN_slowmotion --time_step {fps/TARGET_FPS} --start_frame 1 --end_frame {pngs_generated_count} --frame_input_dir '{FRAME_INPUT_DIR}' --frame_output_dir '{FRAME_OUTPUT_DIR}'" ], "execution_count": 21, "outputs": [ @@ -2703,11 +2522,10 @@ "output_type": "stream", "text": [ "/content/DAIN\n", - "revise the unique id to a random numer 32841\n", - "Namespace(SAVED_MODEL=None, alpha=[0.0, 1.0], arg='./model_weights/32841-Sun-Mar-22-01:38/args.txt', batch_size=1, channels=3, ctx_lr_coe=1.0, datasetName='Vimeo_90K_interp', datasetPath='', dataset_split=97, debug=False, depth_lr_coe=0.001, dtype=, end_frame=11, epsilon=1e-06, factor=0.2, filter_lr_coe=1.0, filter_size=4, flow_lr_coe=0.01, force=False, frame_input_dir='/content/DAIN/input_frames', frame_output_dir='/content/DAIN/output_frames', log='./model_weights/32841-Sun-Mar-22-01:38/log.txt', lr=0.002, netName='DAIN_slowmotion', no_date=False, numEpoch=100, occ_lr_coe=1.0, patience=5, rectify_lr=0.001, save_path='./model_weights/32841-Sun-Mar-22-01:38', save_which=1, seed=1, start_frame=1, time_step=0.18518518518518517, uid=None, use_cuda=True, use_cudnn=1, weight_decay=0, workers=8)\n", + "revise the unique id to a random numer 77090\n", + "Namespace(SAVED_MODEL=None, alpha=[0.0, 1.0], arg='./model_weights/77090-Sun-Mar-22-20:39/args.txt', batch_size=1, channels=3, ctx_lr_coe=1.0, datasetName='Vimeo_90K_interp', datasetPath='', dataset_split=97, debug=False, depth_lr_coe=0.001, dtype=, end_frame=11, epsilon=1e-06, factor=0.2, filter_lr_coe=1.0, filter_size=4, flow_lr_coe=0.01, force=False, frame_input_dir='/content/gdrive/My Drive/DAIN/input_frames', frame_output_dir='/content/gdrive/My Drive/DAIN/output_frames', log='./model_weights/77090-Sun-Mar-22-20:39/log.txt', lr=0.002, netName='DAIN_slowmotion', no_date=False, numEpoch=100, occ_lr_coe=1.0, patience=5, rectify_lr=0.001, save_path='./model_weights/77090-Sun-Mar-22-20:39', save_which=1, seed=1, start_frame=1, time_step=0.18518518518518517, uid=None, use_cuda=True, use_cudnn=1, weight_decay=0, workers=8)\n", "cudnn is used\n", "Interpolate 4 frames\n", - "The testing model weight is: ./model_weights/best.pth\n", "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2506: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.\n", " \"See the documentation of nn.Upsample for details.\".format(mode))\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2722,7 +2540,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 1 | Time per image (avg): 0.00s | Time left: 0:00:00 ******************\n", + "****** Processed frame 1 | Time per frame (avg): 8.38s | Time left: 0:01:23.760271 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2733,7 +2551,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 2 | Time per image (avg): 11.63s | Time left: 0:01:44.663959 ******************\n", + "****** Processed frame 2 | Time per frame (avg): 5.30s | Time left: 0:00:47.687378 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2744,7 +2562,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 3 | Time per image (avg): 6.85s | Time left: 0:00:54.765493 ******************\n", + "****** Processed frame 3 | Time per frame (avg): 4.26s | Time left: 0:00:34.083658 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2755,7 +2573,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 4 | Time per image (avg): 5.26s | Time left: 0:00:36.823278 ******************\n", + "****** Processed frame 4 | Time per frame (avg): 3.74s | Time left: 0:00:26.172509 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2766,7 +2584,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 5 | Time per image (avg): 4.47s | Time left: 0:00:26.809363 ******************\n", + "****** Processed frame 5 | Time per frame (avg): 3.46s | Time left: 0:00:20.735721 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2777,7 +2595,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 6 | Time per image (avg): 3.99s | Time left: 0:00:19.969475 ******************\n", + "****** Processed frame 6 | Time per frame (avg): 3.25s | Time left: 0:00:16.266310 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2788,7 +2606,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 7 | Time per image (avg): 3.68s | Time left: 0:00:14.700462 ******************\n", + "****** Processed frame 7 | Time per frame (avg): 3.12s | Time left: 0:00:12.466697 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2799,7 +2617,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 8 | Time per image (avg): 3.45s | Time left: 0:00:10.342627 ******************\n", + "****** Processed frame 8 | Time per frame (avg): 3.01s | Time left: 0:00:09.018568 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2810,7 +2628,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 9 | Time per image (avg): 3.28s | Time left: 0:00:06.561957 ******************\n", + "****** Processed frame 9 | Time per frame (avg): 2.93s | Time left: 0:00:05.867911 ******************\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", @@ -2821,7 +2639,7 @@ "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", "/pytorch/torch/csrc/autograd/python_function.cpp:622: UserWarning: Legacy autograd function with non-static forward method is deprecated and will be removed in 1.3. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)\n", - "******Processed image 10 | Time per image (avg): 3.15s | Time left: 0:00:03.153109 ******************\n", + "****** Processed frame 10 | Time per frame (avg): 2.87s | Time left: 0:00:02.873018 ******************\n", "Finished processing images.\n" ], "name": "stdout" From c938137d878e26b1e956c946f120bfcd7e68fb96 Mon Sep 17 00:00:00 2001 From: Alpha Date: Sun, 22 Mar 2020 17:15:30 -0400 Subject: [PATCH 7/8] Updated Readme --- README.md | 148 +++++++++++++++++++++++++++++++++++++++++++++++++----- 1 file changed, 136 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index 8a0626f..894fd1e 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,4 @@ -# Overview -This is a modification of DAIN that allows the usage of Google Colab and is able to interpolate frame sequences or videos instead of 2 frames. The original code is limited to interpolation between 2 frames and this code includes a simple fix. - -[Original File by btahir can be found here.](https://github.com/baowenbo/DAIN/issues/44) -This is a modification by Styler00Dollar and [Alpha](https://github.com/AlphaGit). - -Simply copy the Colab_DAIN_alpha.ipynb file to your Google Drive or use this [link](https://colab.research.google.com/drive/1crSsqR_um0GRiDCcVKYobJ-cTIkYe9tq#scrollTo=iGPHW5SOpPe3). - - -### Credits for the original DAIN implementation (Depth-Aware Video Frame Interpolation) +# DAIN (Depth-Aware Video Frame Interpolation) [Project](https://sites.google.com/view/wenbobao/dain) **|** [Paper](http://arxiv.org/abs/1904.00830) [Wenbo Bao](https://sites.google.com/view/wenbobao/home), @@ -29,7 +20,8 @@ This work is developed based on our TPAMI work [MEMC-Net](https://github.com/bao 1. [Testing Pre-trained Models](#testing-pre-trained-models) 1. [Downloading Results](#downloading-results) 1. [Slow-motion Generation](#slow-motion-generation) -1. [Training New Models](#training-new-models) +1. [Training New Models](#training-new-models) +1. [Google Colab Demo](#google-colab-demo) ### Introduction We propose the **D**epth-**A**ware video frame **IN**terpolation (**DAIN**) model to explicitly detect the occlusion by exploring the depth cue. @@ -109,8 +101,140 @@ If you find the code and datasets useful in your research, please cite: year={2018} } +### Requirements and Dependencies +- Ubuntu (We test with Ubuntu = 16.04.5 LTS) +- Python (We test with Python = 3.6.8 in Anaconda3 = 4.1.1) +- Cuda & Cudnn (We test with Cuda = 9.0 and Cudnn = 7.0) +- PyTorch (The customized depth-aware flow projection and other layers require ATen API in PyTorch = 1.0.0) +- GCC (Compiling PyTorch 1.0.0 extension files (.c/.cu) requires gcc = 4.9.1 and nvcc = 9.0 compilers) +- NVIDIA GPU (We use Titan X (Pascal) with compute = 6.1, but we support compute_50/52/60/61 devices, should you have devices with higher compute capability, please revise [this](https://github.com/baowenbo/DAIN/blob/master/my_package/DepthFlowProjection/setup.py)) + +### Installation +Download repository: + + $ git clone https://github.com/baowenbo/DAIN.git + +Before building Pytorch extensions, be sure you have `pytorch >= 1.0.0`: + + $ python -c "import torch; print(torch.__version__)" + +Generate our PyTorch extensions: + + $ cd DAIN + $ cd my_package + $ ./build.sh + +Generate the Correlation package required by [PWCNet](https://github.com/NVlabs/PWC-Net/tree/master/PyTorch/external_packages/correlation-pytorch-master): + + $ cd ../PWCNet/correlation_package_pytorch1_0 + $ ./build.sh + + +### Testing Pre-trained Models +Make model weights dir and Middlebury dataset dir: + + $ cd DAIN + $ mkdir model_weights + $ mkdir MiddleBurySet + +Download pretrained models, + + $ cd model_weights + $ wget http://vllab1.ucmerced.edu/~wenbobao/DAIN/best.pth + +and Middlebury dataset: + + $ cd ../MiddleBurySet + $ wget http://vision.middlebury.edu/flow/data/comp/zip/other-color-allframes.zip + $ unzip other-color-allframes.zip + $ wget http://vision.middlebury.edu/flow/data/comp/zip/other-gt-interp.zip + $ unzip other-gt-interp.zip + $ cd .. + +preinstallations: + + $ cd PWCNet/correlation_package_pytorch1_0 + $ sh build.sh + $ cd ../my_package + $ sh build.sh + $ cd .. + +We are good to go by: + + $ CUDA_VISIBLE_DEVICES=0 python demo_MiddleBury.py + +The interpolated results are under `MiddleBurySet/other-result-author/[random number]/`, where the `random number` is used to distinguish different runnings. + +### Downloading Results +Our DAIN model achieves the state-of-the-art performance on the UCF101, Vimeo90K, and Middlebury ([*eval*](http://vision.middlebury.edu/flow/eval/results/results-n1.php) and *other*). +Dowload our interpolated results with: + + $ wget http://vllab1.ucmerced.edu/~wenbobao/DAIN/UCF101_DAIN.zip + $ wget http://vllab1.ucmerced.edu/~wenbobao/DAIN/Vimeo90K_interp_DAIN.zip + $ wget http://vllab1.ucmerced.edu/~wenbobao/DAIN/Middlebury_eval_DAIN.zip + $ wget http://vllab1.ucmerced.edu/~wenbobao/DAIN/Middlebury_other_DAIN.zip + + +### Slow-motion Generation +Our model is fully capable of generating slow-motion effect with minor modification on the network architecture. +Run the following code by specifying `time_step = 0.25` to generate x4 slow-motion effect: + + $ CUDA_VISIBLE_DEVICES=0 python demo_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step 0.25 + +or set `time_step` to `0.125` or `0.1` as follows + + $ CUDA_VISIBLE_DEVICES=0 python demo_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step 0.125 + $ CUDA_VISIBLE_DEVICES=0 python demo_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step 0.1 +to generate x8 and x10 slow-motion respectively. Or if you would like to have x100 slow-motion for a little fun. + + $ CUDA_VISIBLE_DEVICES=0 python demo_MiddleBury_slowmotion.py --netName DAIN_slowmotion --time_step 0.01 + +You may also want to create gif animations by: + + $ cd MiddleBurySet/other-result-author/[random number]/Beanbags + $ convert -delay 1 *.png -loop 0 Beanbags.gif //1*10ms delay + +Have fun and enjoy yourself! + + +### Training New Models +Download the Vimeo90K triplet dataset for video frame interpolation task, also see [here](https://github.com/anchen1011/toflow/blob/master/download_dataset.sh) by [Xue et al., IJCV19](https://arxiv.org/abs/1711.09078). + + $ cd DAIN + $ mkdir /path/to/your/dataset & cd /path/to/your/dataset + $ wget http://data.csail.mit.edu/tofu/dataset/vimeo_triplet.zip + $ unzip vimeo_triplet.zip + $ rm vimeo_triplet.zip + +Download the pretrained MegaDepth and PWCNet models + + $ cd MegaDepth/checkpoints/test_local + $ wget http://vllab1.ucmerced.edu/~wenbobao/DAIN/best_generalization_net_G.pth + $ cd ../../../PWCNet + $ wget http://vllab1.ucmerced.edu/~wenbobao/DAIN/pwc_net.pth.tar + $ cd .. + +Run the training script: + + $ CUDA_VISIBLE_DEVICES=0 python train.py --datasetPath /path/to/your/dataset --batch_size 1 --save_which 1 --lr 0.0005 --rectify_lr 0.0005 --flow_lr_coe 0.01 --occ_lr_coe 0.0 --filter_lr_coe 1.0 --ctx_lr_coe 1.0 --alpha 0.0 1.0 --patience 4 --factor 0.2 + +The optimized models will be saved to the `model_weights/[random number]` directory, where [random number] is generated for different runs. + +Replace the pre-trained `model_weights/best.pth` model with the newly trained `model_weights/[random number]/best.pth` model. +Then test the new model by executing: + + $ CUDA_VISIBLE_DEVICES=0 python demo_MiddleBury.py + +### Google Colab Demo +This is a modification of DAIN that allows the usage of Google Colab and is able to do a full demo interpolation from a source video to a target video. + +Original Notebook File by btahir can be found [here].(https://github.com/baowenbo/DAIN/issues/44) +This is a modification by [Styler00Dollar](https://github.com/styler00dollar) and [Alpha](https://github.com/AlphaGit). + +Simply upload the `Colab_DAIN_alpha.ipynb` file to your Google Drive or use this [link](https://colab.research.google.com/drive/1crSsqR_um0GRiDCcVKYobJ-cTIkYe9tq#scrollTo=iGPHW5SOpPe3). + ### Contact [Wenbo Bao](mailto:bwb0813@gmail.com); [Wei-Sheng (Jason) Lai](mailto:phoenix104104@gmail.com) ### License -See [MIT License](https://github.com/baowenbo/DAIN/blob/master/LICENSE) +See [MIT License](https://github.com/baowenbo/DAIN/blob/master/LICENSE) \ No newline at end of file From 326a5291e487b29183929dc0b86627b8e9ae0930 Mon Sep 17 00:00:00 2001 From: Alpha Date: Sun, 22 Mar 2020 17:22:31 -0400 Subject: [PATCH 8/8] Markdown typo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 894fd1e..a75d1d1 100644 --- a/README.md +++ b/README.md @@ -228,7 +228,7 @@ Then test the new model by executing: ### Google Colab Demo This is a modification of DAIN that allows the usage of Google Colab and is able to do a full demo interpolation from a source video to a target video. -Original Notebook File by btahir can be found [here].(https://github.com/baowenbo/DAIN/issues/44) +Original Notebook File by btahir can be found [here](https://github.com/baowenbo/DAIN/issues/44). This is a modification by [Styler00Dollar](https://github.com/styler00dollar) and [Alpha](https://github.com/AlphaGit). Simply upload the `Colab_DAIN_alpha.ipynb` file to your Google Drive or use this [link](https://colab.research.google.com/drive/1crSsqR_um0GRiDCcVKYobJ-cTIkYe9tq#scrollTo=iGPHW5SOpPe3).