wehub-resource-sync
69 lines
2.1 KiB
C++
69 lines
2.1 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/roll_grad_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/cpu/roll_kernel_impl.h"
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namespace phi {
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template <typename T, typename Context>
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void RollGradKernel(const Context& dev_ctx,
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const DenseTensor& x UNUSED,
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const DenseTensor& out_grad,
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const IntArray& shifts,
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const std::vector<int64_t>& axis,
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DenseTensor* x_grad) {
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if (x_grad && x_grad->numel() == 0) {
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dev_ctx.template Alloc<T>(x_grad);
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return;
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}
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std::vector<T> out_vec;
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TensorToVector(out_grad, dev_ctx, &out_vec);
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auto shifts_data = shifts.GetData();
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size_t nums = shifts_data.size();
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DDim input_dim = out_grad.dims();
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auto dims = axis;
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// axis = none, reshape to 1-D tensor
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if (dims.empty()) {
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dims.push_back(0l);
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input_dim = Dim<1>(out_vec.size());
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}
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for (size_t i = 0; i < nums; i++) {
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ShiftAlongDim(out_vec.data(), input_dim, dims[i], 0 - shifts_data[i]);
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}
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dev_ctx.template Alloc<T>(x_grad);
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TensorFromVector(out_vec, dev_ctx, x_grad);
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x_grad->Resize(out_grad.dims());
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}
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} // namespace phi
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PD_REGISTER_KERNEL(roll_grad,
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CPU,
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ALL_LAYOUT,
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phi::RollGradKernel,
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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::complex64,
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phi::complex128) {}
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