PyTorch 2.7.1 Release, bug fix release
This release is meant to fix the following issues (regressions / silent correctness):
Torch.compile
Fix Excessive cudagraph re-recording for HF LLM models (#152287) Fix torch.compile on some HuggingFace models (#151154) Fix crash due to Exception raised inside torch.autocast (#152503) Improve Error logging in torch.compile (#149831) Mark mutable custom operators as cacheable in torch.compile (#151194) Implement workaround for a graph break with older version einops (#153925) Fix an issue with tensor.view(dtype).copy_(...) (#151598)
Flex Attention
Fix assertion error due to inductor permuting inputs to flex attention (#151959) Fix performance regression on nanogpt speedrun (#152641)
Distributed
Fix extra CUDA context created by barrier (#149144) Fix an issue related to Distributed Fused Adam in Rocm/APEX when using nccl_ub feature (#150010) Add a workaround random hang in non-blocking API mode in NCCL 2.26 (#154055)
MacOS
Fix MacOS compilation error with Clang 17 (#151316) Fix binary kernels produce incorrect results when one of the tensor arguments is from a wrapped scalar on MPS devices (#152997)
Other
Improve PyTorch Wheel size due to introduction of addition of 128 bit vectorization (#148320) (#152396) Fix fmsub function definition (#152075) Fix Floating point exception in torch.mkldnn_max_pool2d (#151848) Fix abnormal inference output with XPU:1 device (#153067) Fix Illegal Instruction Caused by grid_sample on Windows (#152613) Fix ONNX decomposition does not preserve custom CompositeImplicitAutograd ops (#151826) Fix error with dynamic linking of libgomp library (#150084) Fix segfault in profiler with Python 3.13 (#153848)