Comments (2)
- Job name:
pull / linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build / test (default)
- Credential:
huydhn
Within ~15 minutes, pull / linux-focal-cuda12.1-py3.10-gcc9-experimental-split-build / test (default)
and all of its dependants will be unstable in PyTorch CI. Please verify that the job name looks correct. With great power comes great responsibility.
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I'm seeing the new failure showing on my PR at #128873 (comment)
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Related Issues (20)
- torch parallel Broadcast inconsistency HOT 2
- [PT2E Quantization] Graph with concatenation of the same node will raise RecursionError when prepare_pt2e HOT 6
- [xpu] ERROR: Failed building wheel for triton when USE_XPU=1 make triton HOT 2
- Add comment for label_smoothing parameter in torch.nn.CrossEntropyLoss
- return type of torch.nn.functional.interpolate not working HOT 1
- Incompatability between torch>=2.3 and torchdatasets==0.2.0 HOT 2
- UNSTABLE periodic / win-vs2019-cuda11.8-py3 / test (default) HOT 2
- UNSTABLE periodic / win-vs2019-cuda11.8-py3 / test (default) HOT 1
- frombuffer() → "The given buffer is not writable" warning, tensor has some NaNs HOT 2
- Regression in loading optimizer learning rate HOT 5
- Adding betainc
- take_along_dim or gather unstable results on cpu with stride 1 HOT 2
- Torch Threading causes Seg Fault in pygame. HOT 7
- [inductor][perf] Suboptimal codegen for horizontally fused softmax HOT 4
- [inductor][perf] Inductor/Triton softmax kernel is slower than eager HOT 4
- nn.Linear outputs differ on the same input tensor #129029 answer does not match HOT 2
- interpolate nearest get values zero when outputs over 4G elements
- Questions about CVE-2024-31583 and CVE-2024-31580 HOT 1
- Ignore this
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