search

open-mmlab / mmcv

OpenMMLab Computer Vision Foundation
https://mmcv.readthedocs.io/en/latest/
Apache License 2.0
5.9k stars 1.65k forks source link

mmcv-full installation error #1436

Closed monkeycc closed 3 years ago

monkeycc commented 3 years ago

pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cuda113/torch1.10.0/index.html

.....

                T=std::function<void (const torch::autograd::profiler::thread_event_lists &)>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 别名 模板 实例化“c10::OptionalBase<std::function<void (const torch::autograd::profiler::thread_event_lists &)>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\torch/csrc/autograd/profiler_legacy.h(523): note: 查看对正在编译的 类 模板 实例化“c10::optional<std::function<void (const torch::autograd::profiler::thread_event_lists &)>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(418): warning C4624: “c10::trivially_copyable_optimization_optional_base<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::function<void (const torch::autograd::profiler::thread_event_lists &)>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(184): warning C4624: “c10::constexpr_storage_t<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::vector<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>,std::allocator<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(383): note: 查看对正在编译的 类 模板 实例化“c10::constexpr_storage_t<T>”的引用
            with
            [
                T=std::vector<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>,std::allocator<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 类 模板 实例化“c10::trivially_copyable_optimization_optional_base<T>”的引用
            with
            [
                T=std::vector<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>,std::allocator<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 别名 模板 实例化“c10::OptionalBase<std::vector<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>,std::allocator<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\torch/csrc/autograd/profiler_legacy.h(593): note: 查看对正在编译的 类 模板 实例化“c10::optional<std::vector<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>,std::allocator<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(418): warning C4624: “c10::trivially_copyable_optimization_optional_base<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::vector<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>,std::allocator<std::vector<torch::autograd::profiler::LegacyEvent,std::allocator<torch::autograd::profiler::LegacyEvent>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(184): warning C4624: “c10::constexpr_storage_t<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::vector<std::vector<int64_t,std::allocator<int64_t>>,std::allocator<std::vector<int64_t,std::allocator<int64_t>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(383): note: 查看对正在编译的 类 模板 实例化“c10::constexpr_storage_t<T>”的引用
            with
            [
                T=std::vector<std::vector<int64_t,std::allocator<int64_t>>,std::allocator<std::vector<int64_t,std::allocator<int64_t>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 类 模板 实例化“c10::trivially_copyable_optimization_optional_base<T>”的引用
            with
            [
                T=std::vector<std::vector<int64_t,std::allocator<int64_t>>,std::allocator<std::vector<int64_t,std::allocator<int64_t>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 别名 模板 实例化“c10::OptionalBase<std::vector<std::vector<int64_t,std::allocator<int64_t>>,std::allocator<std::vector<int64_t,std::allocator<int64_t>>>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\torch/csrc/autograd/profiler_kineto.h(40): note: 查看对正在编译的 类 模板 实例化“c10::optional<std::vector<std::vector<int64_t,std::allocator<int64_t>>,std::allocator<std::vector<int64_t,std::allocator<int64_t>>>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(418): warning C4624: “c10::trivially_copyable_optimization_optional_base<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::vector<std::vector<int64_t,std::allocator<int64_t>>,std::allocator<std::vector<int64_t,std::allocator<int64_t>>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(184): warning C4624: “c10::constexpr_storage_t<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::unordered_map<std::string,c10::IValue,std::hash<std::string>,std::equal_to<std::string>,std::allocator<std::pair<const std::string,c10::IValue>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(383): note: 查看对正在编译的 类 模板 实例化“c10::constexpr_storage_t<T>”的引用
            with
            [
                T=std::unordered_map<std::string,c10::IValue,std::hash<std::string>,std::equal_to<std::string>,std::allocator<std::pair<const std::string,c10::IValue>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 类 模板 实例化“c10::trivially_copyable_optimization_optional_base<T>”的引用
            with
            [
                T=std::unordered_map<std::string,c10::IValue,std::hash<std::string>,std::equal_to<std::string>,std::allocator<std::pair<const std::string,c10::IValue>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 别名 模板 实例化“c10::OptionalBase<std::unordered_map<std::string,c10::IValue,std::hash<std::string>,std::equal_to<std::string>,std::allocator<std::pair<const std::string,c10::IValue>>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\torch/csrc/autograd/profiler_kineto.h(48): note: 查看对正在编译的 类 模板 实例化“c10::optional<std::unordered_map<std::string,c10::IValue,std::hash<std::string>,std::equal_to<std::string>,std::allocator<std::pair<const std::string,c10::IValue>>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(418): warning C4624: “c10::trivially_copyable_optimization_optional_base<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::unordered_map<std::string,c10::IValue,std::hash<std::string>,std::equal_to<std::string>,std::allocator<std::pair<const std::string,c10::IValue>>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(184): warning C4624: “c10::constexpr_storage_t<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::vector<at::Tensor,std::allocator<at::Tensor>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(383): note: 查看对正在编译的 类 模板 实例化“c10::constexpr_storage_t<T>”的引用
            with
            [
                T=std::vector<at::Tensor,std::allocator<at::Tensor>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 类 模板 实例化“c10::trivially_copyable_optimization_optional_base<T>”的引用
            with
            [
                T=std::vector<at::Tensor,std::allocator<at::Tensor>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(526): note: 查看对正在编译的 别名 模板 实例化“c10::OptionalBase<std::vector<at::Tensor,std::allocator<at::Tensor>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\torch\csrc\api\include\torch/optim/lbfgs.h(46): note: 查看对正在编译的 类 模板 实例化“c10::optional<std::vector<at::Tensor,std::allocator<at::Tensor>>>”的引用
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\c10/util/Optional.h(418): warning C4624: “c10::trivially_copyable_optimization_optional_base<T>”: 已将析构函数隐式定义为“已删除”
            with
            [
                T=std::vector<at::Tensor,std::allocator<at::Tensor>>
            ]
    E:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\pybind11\detail/common.h(108): warning C4005: “HAVE_SNPRINTF”: 宏重定义
    E:\anaconda3\envs\openmmlab\include\pyerrors.h(490): note: 参见“HAVE_SNPRINTF”的前一个定义
    E:\Cuda112\dev\bin\nvcc.exe -c ./mmcv/ops/csrc/pytorch/cuda\assign_score_withk_cuda.cu -o build\temp.win-amd64-3.7\Release\./mmcv/ops/csrc/pytorch/cuda\assign_score_withk_cuda.obj -IC:\Users\mm\AppData\Local\Temp\pip-install-yxi8m8i9\mmcv-full_c449330eef5c468cb5c6bcf10fa91195\mmcv\ops\csrc\common -IC:\Users\mm\AppData\Local\Temp\pip-install-yxi8m8i9\mmcv-full_c449330eef5c468cb5c6bcf10fa91195\mmcv\ops\csrc\common\cuda -IE:\anaconda3\envs\openmmlab\lib\site-packages\torch\include -IE:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\torch\csrc\api\include -IE:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\TH -IE:\anaconda3\envs\openmmlab\lib\site-packages\torch\include\THC -IE:\Cuda112\dev\include -IE:\anaconda3\envs\openmmlab\include -IE:\anaconda3\envs\openmmlab\include "-ID:\Program Files\Microsoft Visual Studio\2022\Preview\VC\Tools\MSVC\14.30.30423\ATLMFC\include" "-ID:\Program Files\Microsoft Visual Studio\2022\Preview\VC\Tools\MSVC\14.30.30423\include" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.19041.0\ucrt" "-IC:\Program Files (x86)\Windows Kits\10\\include\10.0.19041.0\\shared" "-IC:\Program Files (x86)\Windows Kits\10\\include\10.0.19041.0\\um" "-IC:\Program Files (x86)\Windows Kits\10\\include\10.0.19041.0\\winrt" "-IC:\Program Files (x86)\Windows Kits\10\\include\10.0.19041.0\\cppwinrt" -Xcudafe --diag_suppress=dll_interface_conflict_dllexport_assumed -Xcudafe --diag_suppress=dll_interface_conflict_none_assumed -Xcudafe --diag_suppress=field_without_dll_interface -Xcudafe --diag_suppress=base_class_has_different_dll_interface -Xcompiler /EHsc -Xcompiler /wd4190 -Xcompiler /wd4018 -Xcompiler /wd4275 -Xcompiler /wd4267 -Xcompiler /wd4244 -Xcompiler /wd4251 -Xcompiler /wd4819 -Xcompiler /MD -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=compute_75 -gencode=arch=compute_75,code=sm_75 --use-local-env
    E:\Cuda112\dev\include\crt/host_config.h(160): fatal error C1189: #error:  -- unsupported Microsoft Visual Studio version! Only the versions between 2017 and 2019 (inclusive) are supported! The nvcc flag '-allow-unsupported-compiler' can be used to override this version check; however, using an unsupported host compiler may cause compilation failure or incorrect run time execution. Use at your own risk.
    assign_score_withk_cuda.cu
    error: command 'E:\\Cuda112\\dev\\bin\\nvcc.exe' failed with exit status 2
    ----------------------------------------
ERROR: Command errored out with exit status 1: 'E:\anaconda3\envs\openmmlab\python.exe' -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\mm\\AppData\\Local\\Temp\\pip-install-yxi8m8i9\\mmcv-full_c449330eef5c468cb5c6bcf10fa91195\\setup.py'"'"'; __file__='"'"'C:\\Users\\mm\\AppData\\Local\\Temp\\pip-install-yxi8m8i9\\mmcv-full_c449330eef5c468cb5c6bcf10fa91195\\setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:\Users\mm\AppData\Local\Temp\pip-record-pz4t16ae\install-record.txt' --single-version-externally-managed --compile --install-headers 'E:\anaconda3\envs\openmmlab\Include\mmcv-full' Check the logs for full command output.

addict 2.4.0 albumentations 1.1.0 certifi 2021.10.8 charset-normalizer 2.0.7 click 7.1.2 colorama 0.4.4 cycler 0.10.0 Cython 0.29.24 idna 3.3 imageio 2.9.0 importlib-metadata 4.8.1 instaboostfast 0.1.2 joblib 1.1.0 kiwisolver 1.3.2 lvis 0.5.3 Markdown 3.3.4 matplotlib 3.4.3 mkl-fft 1.3.1 mkl-random 1.2.2 mkl-service 2.4.0 mmcv 1.3.16 mmdet 2.17.0 model-index 0.1.11 networkx 2.6.3 numpy 1.21.2 olefile 0.46 opencv-python 4.5.4.58 opencv-python-headless 4.5.4.58 openmim 0.1.5 ordered-set 4.0.2 packaging 21.0 pandas 1.3.4 Pillow 8.4.0 pip 21.2.4 pycocotools 2.0.2 pycocotools-windows 2.0.0.2 pyparsing 3.0.1 python-dateutil 2.8.2 pytz 2021.3 PyWavelets 1.1.1 PyYAML 6.0 qudida 0.0.4 regex 2021.10.23 requests 2.26.0 scikit-image 0.18.3 scikit-learn 1.0.1 scipy 1.7.1 setuptools 58.0.4 six 1.16.0 tabulate 0.8.9 terminaltables 3.1.0 threadpoolctl 3.0.0 tifffile 2021.10.12 torch 1.10.0 torchaudio 0.10.0 torchvision 0.11.1 typing-extensions 3.10.0.2 urllib3 1.26.7 wheel 0.37.0 wincertstore 0.2 yapf 0.31.0 zipp 3.6.0

zhouzaida commented 3 years ago

hi, we have not provided the pre-built packages for the Windows system, but you can build mmcv-full from source.