/* coding=utf-8 * Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #include #include #include namespace multihead_attn { namespace fused_softmax { namespace scaled_masked_softmax { torch::Tensor fwd_cuda(torch::Tensor const& input, torch::Tensor const& mask, float scale_factor); torch::Tensor bwd_cuda(torch::Tensor const& output_grads, torch::Tensor const& softmax_results, float scale_factor); int get_batch_per_block_cuda(int query_seq_len, int key_seq_len, int batches, int attn_heads); torch::Tensor fwd(torch::Tensor const& input, torch::Tensor const& mask, float scale_factor) { AT_ASSERTM(input.dim() == 4, "expected 4D tensor"); AT_ASSERTM((input.scalar_type() == at::ScalarType::Half) || (input.scalar_type() == at::ScalarType::BFloat16), "Only fp16 and bf16 are supported"); AT_ASSERTM(mask.dim() == 4, "expected 4D tensor"); return fwd_cuda(input, mask, scale_factor); } torch::Tensor bwd(torch::Tensor const& output_grads, torch::Tensor const& softmax_results, float scale_factor) { AT_ASSERTM(output_grads.dim() == 4, "expected 3D tensor"); AT_ASSERTM(softmax_results.dim() == 4, "expected 3D tensor"); AT_ASSERTM((output_grads.scalar_type() == at::ScalarType::Half) || (output_grads.scalar_type() == at::ScalarType::BFloat16), "Only fp16 and bf16 are supported"); AT_ASSERTM((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); } int get_batch_per_block(int query_seq_len, int key_seq_len, int batches, int attn_heads) { return get_batch_per_block_cuda(query_seq_len, key_seq_len, batches, attn_heads); } } // end namespace scaled_masked_softmax } // end namespace fused_softmax } // end namespace multihead_attn PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { m.def("forward", &multihead_attn::fused_softmax::scaled_masked_softmax::fwd, "Self Multihead Attention scaled, time masked softmax -- Forward."); m.def("backward", &multihead_attn::fused_softmax::scaled_masked_softmax::bwd, "Self Multihead Attention scaled, time masked softmax -- Backward."); m.def("get_batch_per_block", &multihead_attn::fused_softmax::scaled_masked_softmax::get_batch_per_block, "Return Batch per block size."); }