wehub-resource-sync
110 lines
3.9 KiB
Plaintext
110 lines
3.9 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 <glog/logging.h>
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#include <thrust/equal.h>
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#include <thrust/execution_policy.h>
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#include "paddle/phi/kernels/elementwise_add_kernel.h"
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#include "paddle/phi/kernels/sparse/elementwise_kernel.h"
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#include "paddle/phi/kernels/sparse/empty_kernel.h"
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#include "paddle/phi/core/enforce.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/visit_type.h"
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namespace phi {
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namespace sparse {
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template <typename T, typename IntT>
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void ElementWiseAddCooGPUKernel(const GPUContext& dev_ctx,
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const SparseCooTensor& x,
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const SparseCooTensor& y,
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SparseCooTensor* out) {
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// TODO(zhangkaiuo): to support universal sparse + sparse
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const auto& x_indices = x.indices();
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const auto& y_indices = y.indices();
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PADDLE_ENFORCE_EQ(
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x_indices.numel(),
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y_indices.numel(),
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common::errors::PreconditionNotMet(
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"The numel of x.indices() and y.indices() should be equal"));
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const IntT* x_indices_ptr = x_indices.data<IntT>();
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const IntT* y_indices_ptr = y_indices.data<IntT>();
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if (VLOG_IS_ON(3)) {
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#ifdef PADDLE_WITH_HIP
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bool is_same = thrust::equal(thrust::hip::par.on(dev_ctx.stream()),
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#else
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bool is_same = thrust::equal(thrust::cuda::par.on(dev_ctx.stream()),
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#endif
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x_indices_ptr,
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x_indices_ptr + x_indices.numel(),
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y_indices_ptr);
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PADDLE_ENFORCE_EQ(
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is_same,
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true,
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common::errors::PreconditionNotMet(
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"Currently, ElementWiseAddCooKernel only supports the case "
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"where x and y have the same indices"));
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}
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EmptyLikeCooKernel<T, GPUContext>(dev_ctx, x, out);
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phi::AddKernel<T, GPUContext>(
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dev_ctx, x.values(), y.values(), out->mutable_values());
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out->SetIndicesDict(x.GetIndicesDict());
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out->SetKmaps(x.GetKmaps());
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}
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template <typename T, typename Context>
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void ElementWiseAddCooKernel(const Context& dev_ctx,
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const SparseCooTensor& x,
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const SparseCooTensor& y,
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SparseCooTensor* out) {
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PD_VISIT_BASE_INTEGRAL_TYPES(x.indices().dtype(), "VerifyIndices", ([&] {
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ElementWiseAddCooGPUKernel<T, data_t>(
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dev_ctx, x, y, out);
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}));
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}
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} // namespace sparse
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} // namespace phi
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PD_REGISTER_KERNEL(add_coo_coo,
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GPU,
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ALL_LAYOUT,
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phi::sparse::ElementWiseAddCooKernel,
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float,
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double,
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int16_t,
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int,
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int64_t,
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phi::float16,
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phi::complex64,
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phi::complex128) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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kernel->InputAt(1).SetDataLayout(phi::DataLayout::SPARSE_COO);
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}
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PD_REGISTER_KERNEL(add_coo_dense,
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GPU,
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ALL_LAYOUT,
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phi::sparse::ElementWiseAddDenseKernel,
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float,
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double,
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int,
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int64_t,
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phi::float16,
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phi::complex64,
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phi::complex128) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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}
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