mirror of
https://github.com/hpcaitech/ColossalAI.git
synced 2025-04-29 12:15:39 +00:00
279300dc5f
* refactor compilation mechanism and unified multi hw * fix file path bug * add init.py to make pybind a module to avoid relative path error caused by softlink * delete duplicated micros * fix micros bug in gcc
55 lines
2.0 KiB
C++
55 lines
2.0 KiB
C++
/*This code from NVIDIA Megatron:
|
|
* with minor changes. */
|
|
|
|
#include <cuda_fp16.h>
|
|
#include <torch/extension.h>
|
|
|
|
#include <vector>
|
|
|
|
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(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);
|
|
}
|
|
|
|
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
|
|
m.def("forward", &fwd,
|
|
"Self Multihead Attention scaled, time masked softmax -- Forward.");
|
|
|
|
m.def("backward", &bwd,
|
|
"Self Multihead Attention scaled, time masked softmax -- Backward.");
|
|
|
|
m.def("get_batch_per_block", &get_batch_per_block,
|
|
"Return Batch per block size.");
|
|
}
|