Comments (1)
@Valentine233 would you mind taking a look at this I was able to narrow this down to _scaled_dot_product_flash_attention_cpu returning NaNs in the forward
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Related Issues (20)
- `torch.tensor()` can also be used with a list of the `float`, `complex` or `bool` type tensors which have a single element each HOT 1
- DISABLED test_deepcopy_after_parametrization_swap_True (__main__.TestNNParametrization) HOT 6
- DISABLED test_output_match___rmatmul___cpu_float32 (__main__.TORCH_NN_MODULECPU) HOT 4
- DISABLED test_output_match___rmatmul___cpu_float32 (__main__.TORCH_EXPORT_EXPORTEDPROGRAMCPU) HOT 2
- RuntimeError using nested tensor in Apple M1 device MPS HOT 3
- [Dynamo] `trials` argument is ignored when using TVM MetaSchedule
- [AOTI] timm_nfnet performs worse than Inductor due to less constant folding optimization
- Gumbel Vector Quantizer produces NaN when using with torch.compile HOT 15
- aot_function cannot handle index_add HOT 3
- profile not record at::meta_xxx time
- DISABLED test_serialization_parametrization_swap_True (__main__.TestNNParametrization) HOT 2
- DISABLED test_pointwise_bessel_y1_cuda (__main__.GPUTests) HOT 2
- nn.Parameter init position HOT 2
- Run existing eager DTensor tests under torch.compile
- Eliminate and test circular imports in PyTorch
- RuntimeError: 0 INTERNAL ASSERT FAILED at "../torch/csrc/jit/ir/alias_analysis.cpp":615, please report a bug to PyTorch. We don't have an op for vulkan_prepack::create_linear_context but it isn't a special case. Argument types: Tensor, Tensor, HOT 2
- ghstack and pytorch-bot can race
- Inductor lowerings for magic methods are suspicious
- "unhashable type: non-nested SymInt" error when using DTensor and Compiled Autograd together HOT 5
- torch.floor_divide throws floating point exception
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