86 lines
2.7 KiB
C++
86 lines
2.7 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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#include "paddle/phi/kernels/array_grad_kernel.h"
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#include "paddle/common/layout.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/concat_grad_kernel.h"
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#include "paddle/phi/kernels/stack_grad_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void TensorToArrayKernel(const Context& dev_ctx,
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const TensorArray& x,
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const DenseTensor& out_grad,
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int axis,
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bool use_stack,
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TensorArray* x_grad) {
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std::vector<DenseTensor> tmp_inputs(x.size());
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std::vector<const DenseTensor*> inputs;
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std::vector<DenseTensor*> inputs_grad;
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std::vector<DenseTensor> tmp_inputs_grad(x.size());
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for (size_t i = 0; i < x.size(); i++) {
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tmp_inputs[i].ShareDataWith(x[i]);
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inputs.push_back(&tmp_inputs[i]);
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inputs_grad.push_back(&tmp_inputs_grad[i]);
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inputs_grad[i]->set_meta(x[i].meta());
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}
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if (use_stack) {
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StackGradKernel<T, Context>(dev_ctx, out_grad, axis, inputs_grad);
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} else {
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ConcatGradKernel<T, Context>(dev_ctx, inputs, out_grad, axis, inputs_grad);
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}
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for (size_t i = 0; i < tmp_inputs_grad.size(); i++) {
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inputs_grad[i] = nullptr;
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x_grad->push_back(tmp_inputs_grad[i]);
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(tensor_to_array,
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CPU,
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ALL_LAYOUT,
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phi::TensorToArrayKernel,
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bool,
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int,
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int64_t,
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float,
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double,
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phi::float16,
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phi::complex64,
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phi::complex128) {}
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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PD_REGISTER_KERNEL(tensor_to_array,
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GPU,
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ALL_LAYOUT,
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phi::TensorToArrayKernel,
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bool,
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int,
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int64_t,
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float,
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double,
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phi::float16,
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phi::complex64,
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phi::complex128) {}
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#endif
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