wehub-resource-sync
103 lines
4.5 KiB
C++
103 lines
4.5 KiB
C++
/* 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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#pragma once
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#include "paddle/phi/kernels/elementwise_add_kernel.h"
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#include "paddle/phi/kernels/sparse/empty_kernel.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/sparse_coo_tensor.h"
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#include "paddle/phi/core/sparse_csr_tensor.h"
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#include "paddle/phi/infermeta/binary.h"
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namespace phi {
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namespace sparse {
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#define DEFINE_ELEMENTWISE_KERNEL_HEAD(name) \
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DEFINE_ELEMENTWISE_KERNEL_HEAD_WITH_TYPE(name, Csr) \
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\
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DEFINE_ELEMENTWISE_KERNEL_HEAD_WITH_TYPE(name, Coo)
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#define DEFINE_ELEMENTWISE_KERNEL_FUNC(name) \
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DEFINE_CSR_ELEMENTWISE_KERNEL_FUNC(name) \
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\
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DEFINE_COO_ELEMENTWISE_KERNEL_FUNC(name)
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#define DEFINE_ELEMENTWISE_KERNEL_HEAD_WITH_TYPE(name, type) \
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template <typename T, typename Context> \
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void ElementWise##name##type##Kernel(const Context& dev_ctx, \
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const Sparse##type##Tensor& x, \
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const Sparse##type##Tensor& y, \
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Sparse##type##Tensor* out);
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#define DEFINE_CSR_ELEMENTWISE_KERNEL_FUNC(name) \
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template <typename T, typename Context> \
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SparseCsrTensor ElementWise##name##Csr(const Context& dev_ctx, \
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const SparseCsrTensor& x, \
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const SparseCsrTensor& y) { \
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DenseTensor crows; \
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DenseTensor cols; \
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DenseTensor values; \
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SparseCsrTensor out(crows, cols, values, x.dims()); \
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MetaTensor meta_out(out); \
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phi::ElementwiseInferMeta(x, y, &meta_out); \
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ElementWise##name##CsrKernel<T, Context>(dev_ctx, x, y, &out); \
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return out; \
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}
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#define DEFINE_COO_ELEMENTWISE_KERNEL_FUNC(name) \
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template <typename T, typename Context> \
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SparseCooTensor ElementWise##name##Coo(const Context& dev_ctx, \
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const SparseCooTensor& x, \
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const SparseCooTensor& y) { \
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DenseTensor indices; \
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DenseTensor values; \
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SparseCooTensor out(indices, values, x.dims()); \
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MetaTensor meta_out(out); \
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phi::ElementwiseInferMeta(x, y, &meta_out); \
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ElementWise##name##CooKernel<T, Context>(dev_ctx, x, y, &out); \
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return out; \
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}
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DEFINE_ELEMENTWISE_KERNEL_HEAD(Add)
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DEFINE_ELEMENTWISE_KERNEL_HEAD(Subtract)
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DEFINE_ELEMENTWISE_KERNEL_HEAD(Multiply)
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DEFINE_ELEMENTWISE_KERNEL_HEAD(Divide)
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DEFINE_ELEMENTWISE_KERNEL_FUNC(Add)
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DEFINE_ELEMENTWISE_KERNEL_FUNC(Subtract)
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DEFINE_ELEMENTWISE_KERNEL_FUNC(Multiply)
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DEFINE_ELEMENTWISE_KERNEL_FUNC(Divide)
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template <typename T, typename Context>
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void ElementWiseAddDenseKernel(const Context& dev_ctx,
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const SparseCooTensor& x,
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const DenseTensor& y,
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SparseCooTensor* out) {
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// TODO(zhangkaiuo): to support universal sparse + dense
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if (y.dims().size() == 1 && y.dims()[0] == x.dims()[x.dims().size() - 1]) {
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EmptyLikeCooKernel<T, Context>(dev_ctx, x, out);
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phi::AddKernel<T, Context>(dev_ctx, x.values(), y, out->mutable_values());
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out->SetIndicesDict(x.GetIndicesDict());
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out->SetKmaps(x.GetKmaps());
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} else {
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PADDLE_THROW(
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errors::Unimplemented("Not support Sparse + Dense in GPU mode"));
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}
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}
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} // namespace sparse
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} // namespace phi
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