sglang_v0.5.2/flashinfer_0.3.1/csrc/group_gemm.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/gemm/group_gemm.cuh>
#include "pytorch_extension_utils.h"
using namespace flashinfer;
using namespace flashinfer::group_gemm;
void CutlassSegmentGEMM(at::Tensor workspace_buffer, at::Tensor all_problems, at::Tensor x_ptr,
at::Tensor w_ptr, at::Tensor y_ptr, at::Tensor x_ld, at::Tensor w_ld,
at::Tensor y_ld, at::Tensor empty_x_data, bool weight_column_major) {
unsigned int batch_size = x_ptr.size(0);
const c10::cuda::OptionalCUDAGuard device_guard(workspace_buffer.device());
auto stream = at::cuda::getCurrentCUDAStream();
DISPATCH_PYTORCH_DTYPE_TO_CTYPE_FP16(empty_x_data.scalar_type(), c_type, [&] {
using cutlass_t = cutlass_dtype_t<c_type>;
auto status = CutlassSegmentGEMMRun<cutlass_t>(
workspace_buffer.data_ptr(), workspace_buffer.element_size() * workspace_buffer.size(0),
all_problems.data_ptr(), batch_size, x_ptr.data_ptr(), w_ptr.data_ptr(), y_ptr.data_ptr(),
x_ld.data_ptr(), w_ld.data_ptr(), y_ld.data_ptr(), weight_column_major, stream);
TORCH_CHECK(status == cudaSuccess,
"Failed to run CutlassSegmentGEMM: ", cudaGetErrorString(status));
return true;
});
}