pytorch

mirror of https://github.com/pytorch/pytorch.git synced 2025-10-20 12:54:11 +08:00

Files

Yu, Guangye 3a110c9bb2 Add a new API torch.xpu.is_tf32_supported for Intel GPU (#163141 )

# Motivation
Aligned with other backends, this PR introduces a new API `torch.xpu.is_tf32_supported`, which should be used before `torch.backends.mkldnn.allow_tf32=True` or provide hardware capability information to the Triton

# Additional Context
On Intel Xe architecture and newer, TF32 operations can be accelerated through DPAS (Dot Product Accumulate Systolic) instructions. Therefore, TF32 support can be determined by checking whether the device supports subgroup matrix multiply-accumulate operations.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163141
Approved by: https://github.com/EikanWang

2025-10-12 12:11:57 +00:00

__init__.py

Add a new API torch.xpu.is_tf32_supported for Intel GPU (#163141 )

2025-10-12 12:11:57 +00:00

_gpu_trace.py

[2/N] Apply ruff UP035 check in torch files (#164054 )

2025-09-29 03:35:32 +00:00

_utils.py

refactor code to share across different devices (#120602 )

2024-02-28 09:42:58 +00:00

memory.py

PEP585 update - torch/nn torch/optim torch/package torch/profiler torch/serialization torch/sparse torch/xpu (#145175 )