sglang_v0.5.2/flashinfer_0.3.1/csrc/cutlass_mla.cu

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/*
* Copyright (c) 2024 by FlashInfer team.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <flashinfer/attention/cutlass_mla.cuh>
#include "pytorch_extension_utils.h"
using namespace flashinfer;
using namespace flashinfer::attention;
void CutlassMLAPagedAttention(at::Tensor workspace, at::Tensor out, at::Tensor lse,
at::Tensor q_nope_pe, at::Tensor ckv_kpe_cache, at::Tensor kv_lens,
at::Tensor page_table) {
const c10::cuda::OptionalCUDAGuard device_guard(q_nope_pe.device());
auto stream = at::cuda::getCurrentCUDAStream();
int device_index = q_nope_pe.device().index();
int batches = q_nope_pe.sizes()[0];
int page_count_per_seq = page_table.sizes()[1];
int page_count_total = ckv_kpe_cache.sizes()[0];
int page_size = ckv_kpe_cache.sizes()[1];
DISPATCH_PYTORCH_DTYPE_TO_CTYPE_FP16(q_nope_pe.scalar_type(), c_type, [&] {
using cutlass_t = cutlass_dtype_t<c_type>;
auto status = runMla<cutlass_t>(
workspace.data_ptr(), out.data_ptr(), lse.data_ptr(), q_nope_pe.data_ptr(),
ckv_kpe_cache.data_ptr(), kv_lens.data_ptr(), page_table.data_ptr(), batches,
page_count_per_seq, page_count_total, page_size, device_index, stream);
TORCH_CHECK(status == cudaSuccess,
"Failed to run CutlassMLAPagedAttention: ", cudaGetErrorString(status));
return true;
});
}