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| #include <cuda_fp16.h> |
| #include <torch/extension.h> |
| #include <vector> |
|
|
| namespace multihead_attn { |
| namespace fused_softmax { |
| namespace scaled_upper_triang_masked_softmax { |
|
|
| torch::Tensor fwd_cuda( |
| torch::Tensor const& input, |
| float scale_factor); |
|
|
| torch::Tensor bwd_cuda( |
| torch::Tensor const& output_grads, |
| torch::Tensor const& softmax_results, |
| float scale_factor); |
|
|
| torch::Tensor fwd(torch::Tensor const& input, float scale_factor) { |
| TORCH_CHECK(input.dim() == 3, "expected 3D tensor"); |
| TORCH_CHECK((input.scalar_type() == at::ScalarType::Half) || |
| (input.scalar_type() == at::ScalarType::BFloat16), |
| "Only fp16 and bf16 are supported"); |
|
|
| return fwd_cuda(input, scale_factor); |
| } |
|
|
| torch::Tensor bwd( |
| torch::Tensor const& output_grads, |
| torch::Tensor const& softmax_results, |
| float scale_factor) { |
|
|
| TORCH_CHECK(output_grads.dim() == 3, "expected 3D tensor"); |
| TORCH_CHECK(softmax_results.dim() == 3, "expected 3D tensor"); |
|
|
| TORCH_CHECK((output_grads.scalar_type() == at::ScalarType::Half) || |
| (output_grads.scalar_type() == at::ScalarType::BFloat16), |
| "Only fp16 and bf16 are supported"); |
| TORCH_CHECK((softmax_results.scalar_type() == at::ScalarType::Half) || |
| (softmax_results.scalar_type() == at::ScalarType::BFloat16), |
| "Only fp16 and bf16 are supported"); |
|
|
| return bwd_cuda(output_grads, softmax_results, scale_factor); |
| } |
|
|
| } |
| } |
| } |
|
|
| PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { |
| m.def("forward", |
| &multihead_attn::fused_softmax::scaled_upper_triang_masked_softmax::fwd, |
| "Self Multihead Attention scaled, time masked softmax -- Forward.", py::call_guard<py::gil_scoped_release>()); |
| m.def("backward", |
| &multihead_attn::fused_softmax::scaled_upper_triang_masked_softmax::bwd, |
| "Self Multihead Attention scaled, time masked softmax -- Backward.", py::call_guard<py::gil_scoped_release>()); |
| } |
|
|