wehub-resource-sync
81 lines
2.6 KiB
C++
81 lines
2.6 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include "paddle/phi/kernels/add_n_kernel.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/tensor_utils.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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#include "paddle/phi/kernels/funcs/selected_rows_functor.h"
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namespace phi {
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template <typename T, typename Context>
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void AddNArrayKernel(const Context& dev_ctx,
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const std::vector<const TensorArray*>& x,
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TensorArray* out) {
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for (auto& ele : *out) {
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dev_ctx.template Alloc<T>(&ele);
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}
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bool in_place = true;
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if (x.size() > 0 && x[0]->size() == out->size()) {
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for (size_t i = 0; i < out->size(); i++) {
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if (x[0]->at(i).IsInitialized() &&
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out->at(i).data() != x[0]->at(i).data()) {
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in_place = false;
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break;
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}
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}
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} else {
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in_place = false;
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}
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for (size_t i = in_place ? 1 : 0; i < x.size(); ++i) {
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auto* in_array = x.at(i);
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for (size_t j = 0; j < in_array->size(); ++j) {
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if (in_array->at(j).IsInitialized() && (in_array->at(j).numel() != 0)) {
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if (j >= out->size()) {
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out->resize(j + 1);
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}
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if (!out->at(j).IsInitialized() || (out->at(j).numel() == 0)) {
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Copy<Context>(dev_ctx,
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in_array->at(j),
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in_array->at(j).place(),
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false,
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&out->at(j));
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out->at(j).set_lod(in_array->at(j).lod());
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} else {
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PADDLE_ENFORCE_EQ(
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out->at(j).lod(),
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in_array->at(j).lod(),
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common::errors::InvalidArgument(
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"The lod message between inputs[%d] and"
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" outputs[%d] must be same, but now is not same.",
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j,
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j));
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auto in = EigenVector<T>::Flatten(in_array->at(j));
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auto result = EigenVector<T>::Flatten(out->at(j));
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result.device(*dev_ctx.eigen_device()) = result + in;
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}
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}
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}
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}
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}
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} // namespace phi
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