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/* coding=utf-8
* Copyright (c) 2020, 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 <cuda_fp16.h>
#include <torch/extension.h>
#include <vector>
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."
);
}
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