gpt-neox

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/* coding=utf-8
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 * Copyright (c) 2024, NVIDIA CORPORATION.  All rights reserved.
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 *
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 * Licensed under the Apache License, Version 2.0 (the "License");
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 * you may not use this file except in compliance with the License.
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 * You may obtain a copy of the License at
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 *
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 *     http://www.apache.org/licenses/LICENSE-2.0
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 *
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 * Unless required by applicable law or agreed to in writing, software
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 * distributed under the License is distributed on an "AS IS" BASIS,
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 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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 * See the License for the specific language governing permissions and
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 * limitations under the License.
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 */
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#include <cuda_fp16.h>
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#include <torch/extension.h>
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#include <vector>
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namespace multihead_attn {
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namespace fused_softmax {
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namespace scaled_masked_softmax {
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torch::Tensor fwd_cuda(torch::Tensor const& input, torch::Tensor const& mask, float scale_factor);
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torch::Tensor bwd_cuda(torch::Tensor const& output_grads,
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                       torch::Tensor const& softmax_results,
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                       float scale_factor);
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int get_batch_per_block_cuda(int query_seq_len, int key_seq_len, int batches, int attn_heads);
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torch::Tensor fwd(torch::Tensor const& input, torch::Tensor const& mask, float scale_factor)
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{
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    AT_ASSERTM(input.dim() == 4, "expected 4D tensor");
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    AT_ASSERTM((input.scalar_type() == at::ScalarType::Half) ||
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                   (input.scalar_type() == at::ScalarType::BFloat16),
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               "Only fp16 and bf16 are supported");
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    AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
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    return fwd_cuda(input, mask, scale_factor);
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}
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torch::Tensor bwd(torch::Tensor const& output_grads,
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                  torch::Tensor const& softmax_results,
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                  float scale_factor)
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{
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    AT_ASSERTM(output_grads.dim() == 4, "expected 3D tensor");
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    AT_ASSERTM(softmax_results.dim() == 4, "expected 3D tensor");
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    AT_ASSERTM((output_grads.scalar_type() == at::ScalarType::Half) ||
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                   (output_grads.scalar_type() == at::ScalarType::BFloat16),
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               "Only fp16 and bf16 are supported");
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    AT_ASSERTM((softmax_results.scalar_type() == at::ScalarType::Half) ||
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                   (softmax_results.scalar_type() == at::ScalarType::BFloat16),
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               "Only fp16 and bf16 are supported");
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    return bwd_cuda(output_grads, softmax_results, scale_factor);
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}
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int get_batch_per_block(int query_seq_len, int key_seq_len, int batches, int attn_heads)
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{
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    return get_batch_per_block_cuda(query_seq_len, key_seq_len, batches, attn_heads);
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}
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}  // end namespace scaled_masked_softmax
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}  // end namespace fused_softmax
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}  // end namespace multihead_attn
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)
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{
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    m.def("forward",
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          &multihead_attn::fused_softmax::scaled_masked_softmax::fwd,
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          "Self Multihead Attention scaled, time masked softmax -- Forward.");
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    m.def("backward",
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          &multihead_attn::fused_softmax::scaled_masked_softmax::bwd,
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          "Self Multihead Attention scaled, time masked softmax -- Backward.");
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    m.def("get_batch_per_block",
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          &multihead_attn::fused_softmax::scaled_masked_softmax::get_batch_per_block,
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          "Return Batch per block size.");
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}
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