![]() ![]() Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -O2 -fPIC -Wno-narrowing -Wall -Wextra -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math, DISABLE_NUMA=1, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, USE_CUDA=True, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=True, USE_NNPACK=True, USE_OPENMP=ON, NVCC architecture flags: -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_50,code=compute_50 Intel(R) Math Kernel Library Version 2019.0.4 Product Build 20190411 for Intel(R) 64 architecture applications The compute capability is unfortunately not encoded in the file names, so the best approach would be to install the binary and just see, if your GPU works, or print: print(torch._config_.show()) Thanks for helping clear these things up for me. tar.bz2 files are linux binaries, while the To determine its minimum required compute capability (before Potentially support compute capability 2.0 – 6.2? Is there any Pytorch_legacy-0.1.12-p圓5_0.1.2.Īm I right that the “cu80” part of the file name suggests that theīinary is built with CUDA SDK 8.0 and that it could therefore ![]() In a similar vein, do you know how I mightįigure out which of these binaries support which compute capability?įor example, the first file on that google drive is However, if you would like to play around with some legacy PyTorch version, you might get lucky finding some supported binaries here (built by for that link. Is there any way for meĭeduce whether such a download will support computeĬapability 3.0, or whether it starts earliest at 3.5? START LOCALLY” section, one is given the choice of CUDAĩ.0 and 10.0 (and none), which I suppose I now understand If I’m not mistaken, the minimal compute capability for the current binaries is >=3.5,ĭo you know how I might determine which compute capability aįor example, on the main page, in the “QUICK Thanks for clearing up that confusion of mine. I was referring to compute capability 3.0 (not that I knew I assume you are referring to the compute capability 3.0, which should work with CUDA6.0 - CUDA10.1.
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