ColossalAI/extensions/pybind/softmax/scaled_masked_softmax.cpp

/*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.");
}