41 lines
1.8 KiB
Plaintext
41 lines
1.8 KiB
Plaintext
/*
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* Copyright (c) 2024 by FlashInfer team.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <flashinfer/gemm/group_gemm.cuh>
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#include "pytorch_extension_utils.h"
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using namespace flashinfer;
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using namespace flashinfer::group_gemm;
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void CutlassSegmentGEMM(at::Tensor workspace_buffer, at::Tensor all_problems, at::Tensor x_ptr,
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at::Tensor w_ptr, at::Tensor y_ptr, at::Tensor x_ld, at::Tensor w_ld,
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at::Tensor y_ld, at::Tensor empty_x_data, bool weight_column_major) {
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unsigned int batch_size = x_ptr.size(0);
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const c10::cuda::OptionalCUDAGuard device_guard(workspace_buffer.device());
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auto stream = at::cuda::getCurrentCUDAStream();
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DISPATCH_PYTORCH_DTYPE_TO_CTYPE_FP16(empty_x_data.scalar_type(), c_type, [&] {
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using cutlass_t = cutlass_dtype_t<c_type>;
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auto status = CutlassSegmentGEMMRun<cutlass_t>(
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workspace_buffer.data_ptr(), workspace_buffer.element_size() * workspace_buffer.size(0),
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all_problems.data_ptr(), batch_size, x_ptr.data_ptr(), w_ptr.data_ptr(), y_ptr.data_ptr(),
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x_ld.data_ptr(), w_ld.data_ptr(), y_ld.data_ptr(), weight_column_major, stream);
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TORCH_CHECK(status == cudaSuccess,
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"Failed to run CutlassSegmentGEMM: ", cudaGetErrorString(status));
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return true;
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});
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}
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