Don't initialize the current device in CUDAGenerator::CUDAGenerator#7392
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ezyang
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May 8, 2018
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Can we add a test that checks for this unwanted init? It's not the first time we get this regression. |
Previously, CUDAGenerator::CUDAGenerator would initialize the random number generator on the current device. This would usually be device 0. This is undesirable because initialize the CUDA context allocates a few 100 MBs due to all the kernels in libTHC.so. This avoids the unecessary call to THCRandom_getGenerator() in the CUDAGenerator constructor. Fixes pytorch#7320
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…e in CUDAGenerator::CUDAGenerator (pytorch/pytorch#7392) pytorch/pytorch@976b1d5
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@colesbury unfortunately cuda runtime API ignore the existence of contexts alltogether, so there's no way to query context using them. |
weiyangfb
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Jun 11, 2018
…ytorch#7392) Previously, CUDAGenerator::CUDAGenerator would initialize the random number generator on the current device. This would usually be device 0. This is undesirable because initialize the CUDA context allocates a few 100 MBs due to all the kernels in libTHC.so. This avoids the unecessary call to THCRandom_getGenerator() in the CUDAGenerator constructor. Fixes pytorch#7320 Previously, CUDAGenerator::CUDAGenerator would initialize the random number generator on the current device. This would usually be device 0. This is undesirable because initialize the CUDA context allocates a few 100 MBs due to all the kernels in libTHC.so. This avoids the unecessary call to THCRandom_getGenerator() in the CUDAGenerator constructor. Fixes pytorch#7320 * Fix call to get THCState
laurentdupin
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Apr 24, 2026
…ytorch#7392) Previously, CUDAGenerator::CUDAGenerator would initialize the random number generator on the current device. This would usually be device 0. This is undesirable because initialize the CUDA context allocates a few 100 MBs due to all the kernels in libTHC.so. This avoids the unecessary call to THCRandom_getGenerator() in the CUDAGenerator constructor. Fixes pytorch#7320 Previously, CUDAGenerator::CUDAGenerator would initialize the random number generator on the current device. This would usually be device 0. This is undesirable because initialize the CUDA context allocates a few 100 MBs due to all the kernels in libTHC.so. This avoids the unecessary call to THCRandom_getGenerator() in the CUDAGenerator constructor. Fixes pytorch#7320 * Fix call to get THCState
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Previously, CUDAGenerator::CUDAGenerator would initialize the random
number generator on the current device. This would usually be device 0.
This is undesirable because initialize the CUDA context allocates a few
100 MBs due to all the kernels in libTHC.so.
This avoids the unecessary call to THCRandom_getGenerator() in the
CUDAGenerator constructor.
Fixes #7320