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ColossalAI/extensions/csrc/cuda/pybind/scaled_masked_softmax.cpp

71 lines
2.6 KiB

/*This code from NVIDIA Megatron:
* with minor changes. */
#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.");
}