mirror of https://github.com/hpcaitech/ColossalAI
71 lines
2.6 KiB
C++
71 lines
2.6 KiB
C++
/*This code from NVIDIA Megatron:
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* with minor changes. */
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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,
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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,
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int attn_heads);
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torch::Tensor fwd(torch::Tensor const& input, torch::Tensor const& mask,
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float scale_factor) {
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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, float scale_factor) {
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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,
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int attn_heads) {
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return get_batch_per_block_cuda(query_seq_len, key_seq_len, batches,
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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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m.def("forward", &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", &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::
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get_batch_per_block,
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"Return Batch per block size.");
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}
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