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