wehub-resource-sync
84 lines
3.0 KiB
Plaintext
84 lines
3.0 KiB
Plaintext
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include "paddle/phi/kernels/sparse/mv_kernel.h"
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#include "paddle/common/ddim.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/sparse/sparse_blas.h"
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namespace phi {
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namespace sparse {
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template <typename T, typename Context, typename TensorType>
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void MvKernelImpl(const Context& dev_ctx,
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const TensorType& x,
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const DenseTensor& vec,
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DenseTensor* out) {
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#if defined(PADDLE_WITH_CUDA)
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std::vector<int64_t> x_dim = vectorize(x.dims());
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std::vector<int64_t> vec_dim = vectorize(vec.dims());
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auto x_ndims = x_dim.size();
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auto vec_ndims = vec_dim.size();
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PADDLE_ENFORCE_EQ(x_ndims,
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2,
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common::errors::InvalidArgument(
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"the dims size of Input(x) must be equal to 2."));
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PADDLE_ENFORCE_EQ(vec_ndims,
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1,
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common::errors::InvalidArgument(
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"the dims size of Input(vec) must be equal to 1."));
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PADDLE_ENFORCE_EQ(x_dim[x_ndims - 1],
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vec_dim[vec_ndims - 1],
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common::errors::PreconditionNotMet(
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"The shape of Input(x) and Input(vec) is not "
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"suitable for mv operation, "
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"x_dim[-1] must be equal to vec_dim[-1]."));
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std::vector<int64_t> out_dim = {x_dim[x_ndims - 2]};
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out->Resize(out_dim);
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dev_ctx.template Alloc<T>(out);
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auto sparse_blas = funcs::sparse::GetSparseBlas<Context, T>(dev_ctx);
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sparse_blas.SPMV(false, static_cast<T>(1), x, vec, static_cast<T>(0), out);
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#endif
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}
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template <typename T, typename Context>
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void MvCooKernel(const Context& dev_ctx,
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const SparseCooTensor& x,
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const DenseTensor& vec,
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DenseTensor* out) {
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MvKernelImpl<T>(dev_ctx, x, vec, out);
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}
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template <typename T, typename Context>
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void MvCsrKernel(const Context& dev_ctx,
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const SparseCsrTensor& x,
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const DenseTensor& vec,
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DenseTensor* out) {
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MvKernelImpl<T>(dev_ctx, x, vec, out);
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}
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} // namespace sparse
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} // namespace phi
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PD_REGISTER_KERNEL(
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mv_csr, GPU, ALL_LAYOUT, phi::sparse::MvCsrKernel, float, double) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR);
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}
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PD_REGISTER_KERNEL(
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mv_coo, GPU, ALL_LAYOUT, phi::sparse::MvCooKernel, float, double) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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}
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