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install_requirements.py

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@@ -71,7 +71,7 @@ def python_is_compatible():
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#
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# NOTE: If you're changing, make the corresponding change in .ci/docker/ci_commit_pins/pytorch.txt
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# by picking the hash from the same date in https://hud.pytorch.org/hud/pytorch/pytorch/nightly/
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NIGHTLY_VERSION = "dev20250422"
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NIGHTLY_VERSION = "dev20250527"
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def install_requirements(use_pytorch_nightly):

runtime/core/portable_type/c10/c10/macros/Macros.h

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@@ -241,7 +241,7 @@ using namespace c10::xpu;
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#ifdef __HIPCC__
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// Unlike CUDA, HIP requires a HIP header to be included for __host__ to work.
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// We do this #include here so that C10_HOST_DEVICE and friends will Just Work.
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// See https://github.com/ROCm-Developer-Tools/HIP/issues/441
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// See https://github.com/ROCm/hip/issues/441
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#include <hip/hip_runtime.h>
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#endif
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@@ -286,7 +286,7 @@ constexpr uint32_t CUDA_THREADS_PER_BLOCK_FALLBACK = 256;
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#define C10_MIN_BLOCKS_PER_SM(threads_per_block, blocks_per_sm) \
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((((threads_per_block) * (blocks_per_sm) <= CUDA_MAX_THREADS_PER_SM) \
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? (blocks_per_sm) \
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: ((CUDA_MAX_THREADS_PER_SM + (threads_per_block)-1) / \
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: ((CUDA_MAX_THREADS_PER_SM + (threads_per_block) - 1) / \
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(threads_per_block))))
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// C10_LAUNCH_BOUNDS is analogous to __launch_bounds__
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#define C10_LAUNCH_BOUNDS_0 \

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