Workaround arm64 gcc error in std::copysign
#51900
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Move definition of copysign template and specialization for bfloat16/half types before first use of copysign in that file Add comment explaining why this is necessary Fixes pytorch#51889
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Summary: Move definition of copysign template and specialization for bfloat16/half types before first use of copysign in that file Add comment explaining why this is necessary Fixes pytorch#51889 Pull Request resolved: pytorch#51900 Reviewed By: walterddr Differential Revision: D26321741 Pulled By: malfet fbshipit-source-id: 888858b11d9708fa140fe9c0570cc5a24599205b
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Summary: Move definition of copysign template and specialization for bfloat16/half types before first use of copysign in that file Add comment explaining why this is necessary Fixes #51889 Pull Request resolved: #51900 Reviewed By: walterddr Differential Revision: D26321741 Pulled By: malfet fbshipit-source-id: 888858b11d9708fa140fe9c0570cc5a24599205b
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… / 8 for CUDA (#51834) Summary: It seems that the std::copysign code introduced in #51706 is too much for gcc 7.5 / 8 when compiled on arm64 (e.g. on Jetson with latest Jetpack) and causes it to produce an internal compiler error with segfault during compilation. This avoids the compiler bug it by not using std::copysign. A very kind person sent a Jetson Xavier NX {emoji:1f381} thank you {emoji:2764}. After #51900 fixed this for CPU-only arm64 (eg Raspberry), this fixes it for CUDA-using arm64 (e.g. Jetson). CUDA device lambdas must also be present as host functions for technical reasons but they are never used, so we just assert in the CPU variant instead of actually doing the operation. Pull Request resolved: #51834 Reviewed By: mrshenli Differential Revision: D27622277 Pulled By: malfet fbshipit-source-id: a1dc4c3a67f925019782e24b796919e17339749f
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… / 8 for CUDA (pytorch#51834) Summary: It seems that the std::copysign code introduced in pytorch#51706 is too much for gcc 7.5 / 8 when compiled on arm64 (e.g. on Jetson with latest Jetpack) and causes it to produce an internal compiler error with segfault during compilation. This avoids the compiler bug it by not using std::copysign. A very kind person sent a Jetson Xavier NX {emoji:1f381} thank you {emoji:2764}. After pytorch#51900 fixed this for CPU-only arm64 (eg Raspberry), this fixes it for CUDA-using arm64 (e.g. Jetson). CUDA device lambdas must also be present as host functions for technical reasons but they are never used, so we just assert in the CPU variant instead of actually doing the operation. Pull Request resolved: pytorch#51834 Reviewed By: mrshenli Differential Revision: D27622277 Pulled By: malfet fbshipit-source-id: a1dc4c3a67f925019782e24b796919e17339749f
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Move definition of copysign template and specialization for
bfloat16/half types before first use of copysign in that file
Add comment explaining why this is necessary
Fixes #51889