wehub-resource-sync
84 lines
2.7 KiB
Plaintext
84 lines
2.7 KiB
Plaintext
// 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/kernels/gpu/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,
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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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auto* out_grad_data = out_grad.data<T>();
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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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T* x_grad_data = dev_ctx.template Alloc<T>(x_grad);
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auto shifts_data = shifts.GetData();
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int rank = shifts_data.size();
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int64_t numel = out_grad.numel();
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auto input_dim = out_grad.dims();
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auto stride_dim = common::stride(input_dim);
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std::vector<int64_t> strides(rank), sizes(rank);
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if (axis.size() == 0) {
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strides[0] = 1;
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sizes[0] = numel;
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shifts_data[0] = ((-shifts_data[0]) % numel + numel) % numel;
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} else {
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for (int i = 0; i < rank; i++) {
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int dim = axis[i] >= 0 ? axis[i] : axis[i] + input_dim.size();
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int64_t size = input_dim[dim];
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if (size != 0) {
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shifts_data[i] = ((-shifts_data[i]) % size + size) % size;
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strides[i] = stride_dim[dim];
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sizes[i] = size;
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}
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}
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}
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LaunchRollKernel<T, Context>(dev_ctx,
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out_grad_data,
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x_grad_data,
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rank,
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numel,
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shifts_data,
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strides,
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sizes);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(roll_grad,
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GPU,
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ALL_LAYOUT,
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phi::RollGradKernel,
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phi::float16,
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phi::bfloat16,
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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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