chore: import upstream snapshot with attribution
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// 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 <string>
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#include "paddle/phi/common/place.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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#include "paddle/phi/kernels/funcs/segment_pooling.h"
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namespace phi {
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template <typename T, typename Context>
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void SegmentPoolGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& segment_ids,
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const DenseTensor& out,
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const optional<DenseTensor>& summed_ids,
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const DenseTensor& out_grad,
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const std::string& pooltype,
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DenseTensor* x_grad) {
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dev_ctx.template Alloc<T>(x_grad);
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funcs::SetConstant<Context, T> set_zero;
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set_zero(dev_ctx, x_grad, static_cast<T>(0));
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// return after allocation if x_grad is empty.
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if (x_grad && x_grad->numel() == 0) {
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return;
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}
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auto index_type = segment_ids.type();
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if (index_type == DataType::INT32) {
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funcs::SegmentPoolGradFunctor<Context, T, int> pool;
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pool(dev_ctx, x, out, out_grad, segment_ids, x_grad, summed_ids, pooltype);
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} else if (index_type == DataType::INT64) {
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funcs::SegmentPoolGradFunctor<Context, T, int64_t> pool;
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pool(dev_ctx, x, out, out_grad, segment_ids, x_grad, summed_ids, pooltype);
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} else {
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PADDLE_THROW(common::errors::InvalidArgument(
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"Unsupported index type, Expected int, int64, but got %s.",
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index_type));
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}
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}
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} // namespace phi
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