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Lift jagged -> padded dense forward / backward kernels from fbgemm_gpu #125946

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Lift jagged -> padded dense forward / backward kernels from fbgemm_gpu #125946

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Lift jagged -> padded dense forward / backward kernels from fbgemm_gpu
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10 changes: 10 additions & 0 deletions aten/src/ATen/native/native_functions.yaml
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Expand Up @@ -14644,6 +14644,16 @@
NestedTensorCUDA: NestedTensor_to_padded_tensor_cuda
autogen: to_padded_tensor.out

- func: _jagged_to_padded_dense_forward(Tensor values, Tensor[] offsets, SymInt[] max_lengths, float padding_value=0.0) -> Tensor
variants: function
dispatch:
CUDA: _fbgemm_jagged_to_padded_dense_forward

- func: _padded_dense_to_jagged_forward(Tensor dense, Tensor[] offsets, SymInt? total_L=None) -> Tensor
variants: function
dispatch:
CUDA: _fbgemm_dense_to_jagged_forward_symint
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IIRC, some variants of padded_dense_to_jagged_forward also take a padding value, in case any of your sequences are longer than the sequence dimension of the dense tensor. I guess we probably don't care too much about this right now though?

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this is a good point - I think for our initial op coverage purposes, we don't care too much. we may need to revisit this for more general usages though


- func: _nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor
dispatch:
NestedTensorCPU: NestedTensor_softmax_dropout
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