Conversation
| # compute stream or in other cases kernels actually launching from the | ||
| # main thread. | ||
| self._staging_stream = torch.cuda.Stream() | ||
| self._staging_stream = torch.Stream() |
Collaborator
There was a problem hiding this comment.
what will happen to do sync with such stream?
Owner
Author
There was a problem hiding this comment.
When set non-blocking=True, this stream ensure copy done. isn’t used anywhere else.
| assert torch.cuda.is_available(), "Non-blocking copy requires CUDA" | ||
| if self._config.use_non_blocking_copy: | ||
| assert torch.accelerator.is_available(), ( | ||
| "Non-blocking copy requires CUDA/XPU" |
Collaborator
There was a problem hiding this comment.
What's the limitation to require non-blocking? Must to be accelerator?
Owner
Author
There was a problem hiding this comment.
non-blocking only used for copy between CPU and GPU, I assume all accelerator support.
Co-authored-by: Yu, Guangye <106960996+guangyey@users.noreply.github.com>
Co-authored-by: Yu, Guangye <106960996+guangyey@users.noreply.github.com>
Co-authored-by: Yu, Guangye <106960996+guangyey@users.noreply.github.com>
pytorchmergebot
force-pushed
the
xpu_stage
branch
from
July 24, 2025 02:51
5298813 to
615fb77
Compare
Chao1Han
pushed a commit
that referenced
this pull request
Mar 16, 2026
…nces between x86 vs aarch64 (pytorch#176085) In the test: ``` python test/cpp_extensions/test_libtorch_agnostic.py TestLibtorchAgnosticCUDA.test_std_cuda_check_error_show_cpp_stacktraces_True_cuda ``` it raises an exception when calling `STD_CUDA_CHECK(cudaSetDevice(99999));` which got the expected `CUDA error: invalid device` message. However, the expected string for the C++ stack trace is different between `x86` vs `aarch64` due perhaps in these issues: - pytorch#119905 - pytorch#134387 In the current setup when getting a stack trace string: - x86 contains `C++ CapturedTraceback:` - aarch64 contains `Exception raised from` + `frame #` An example of the full string from an aarch64 system when : ``` AssertionError: 'C++ CapturedTraceback:' not found in 'CUDA error: invalid device ordinal\nGPU device may be out of range, do you have enough GPUs?\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1\nCompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n\nException raised from test_std_cuda_check_error at /opt/pytorch/pytorch/test/cpp_extensions/libtorch_agn_2_10_extension/csrc/test_std_cuda_check.cu:23 (most recent call first):\nframe #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0xd4 (0xe471ebcd39f4 in /usr/local/lib/python3.12/dist-packages/torch/lib/libc10.so)\nframe #1: <unknown function> + 0x43f998 (0xe471ebdcf998 in /usr/local/lib/python3.12/dist-packages/torch/lib/libc10_cuda.so)\nframe #2: c10::cuda::c10_cuda_check_implementation(int, char const*, char const*, unsigned int, bool) + 0x1bc (0xe471ebdcfc0c in /usr/local/lib/python3.12/dist-packages/torch/lib/libc10_cuda.so)\nframe #3: torch_c10_cuda_check_msg + 0x1c (0xe471ef335c4c in /usr/local/lib/python3.12/dist-packages/torch/lib/libtorch_cuda.so)\nframe #4: test_std_cuda_check_error() + 0x58 (0xe470cd396678 in /opt/pytorch/pytorch/test/cpp_extensions/libtorch_agn_2_10_extension/install/usr/local/lib/python3.12/dist-packages/libtorch_agn_2_10/_C.so)\nframe #5: c10::BoxedKernel::makeFromFunctor<StableIValueBoxedKernel>(std::unique_ptr<StableIValueBoxedKernel, std::default_delete<StableIValueBoxedKernel> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)#1}::_FUN(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) + 0x16c (0xe47211cd419c in /usr/local/lib/python3.12/dist-packages/torch/lib/libtorch_cpu.so)\nframe #6: <unknown function> + 0x61d34bc (0xe47211cf34bc in /usr/local/lib/python3.12/dist-packages/torch/lib/libtorch_cpu.so)\nframe #7: <unknown function> + 0xe6c324 (0xe4721532c324 in /usr/local/lib/python3.12/dist-packages/torch/lib/libtorch_python.so)\nframe #8: <unknown function> + 0xe6c7e0 (0xe4721532c7e0 in /usr/local/lib/python3.12/dist-packages/torch/lib/libtorch_python.so)\nframe #9: <unknown function> + 0xd3907c (0xe472151f907c in /usr/local/lib/python3.12/dist-packages/torch/lib/libtorch_python.so)\nframe #10: <unknown function> + 0x5ccbf8 (0xe47214a8cbf8 in /usr/local/lib/python3.12/dist-packages/torch/lib/libtorch_python.so)\nframe #11: /usr/bin/python() [0x504a34]\nframe #12: PyObject_Call + 0x6c (0x4c633c in /usr/bin/python)\nframe #13: _PyEval_EvalFrameDefault + 0x3ea0 (0x568564 in /usr/bin/python)\nframe #14: _PyObject_Call_Prepend + 0xc4 (0x4c5934 in /usr/bin/python)\nframe #15: /usr/bin/python() [0x52a070]\nframe #16: _PyObject_MakeTpCall + 0x78 (0x4c3e58 in /usr/bin/python)\nframe #17: _PyEval_EvalFrameDefault + 0x8a0 (0x564f64 in /usr/bin/python)\nframe #18: PyEval_EvalCode + 0x130 (0x5632b4 in /usr/bin/python)\nframe #19: PyRun_StringFlags + 0xe0 (0x59c330 in /usr/bin/python)\nframe #20: PyRun_SimpleStringFlags + 0x44 (0x67ebc4 in /usr/bin/python)\nframe #21: Py_RunMain + 0x390 (0x68b380 in /usr/bin/python)\nframe #22: Py_BytesMain + 0x28 (0x68ae88 in /usr/bin/python)\nframe #23: <unknown function> + 0x284c4 (0xe47216b084c4 in /lib/aarch64-linux-gnu/libc.so.6)\nframe #24: __libc_start_main + 0x98 (0xe47216b08598 in /lib/aarch64-linux-gnu/libc.so.6)\nframe #25: _start + 0x30 (0x5f6770 in /usr/bin/python)\n\n' To execute this test, run the following from the base repo dir: python test/cpp_extensions/test_libtorch_agnostic.py TestLibtorchAgnosticCUDA.test_std_cuda_check_error_show_cpp_stacktraces_True_cuda ``` Pull Request resolved: pytorch#176085 Approved by: https://github.com/eqy
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Enable device-agnostic implementation of DCP-related functionality, allowing the new DCP features to be supported on XPU as well.
use_cuda_non_blocking_copy to use_non_blocking_copy because non-blocking copy is supported by most GPUs and is not exclusive to CUDA devices.
Test plan: test cases have not yet been updated to be fully device agnostic; this will be addressed in future work.