wehub-resource-sync
66 lines
2.1 KiB
C++
66 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/fill_diagonal_grad_kernel.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/common_shape.h"
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namespace phi {
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template <typename T, typename Context>
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void FillDiagonalGradKernel(const Context& dev_ctx,
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const DenseTensor& out_grad,
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float value UNUSED,
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int offset,
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bool wrap,
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DenseTensor* x_grad) {
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if (x_grad) {
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T* data = dev_ctx.template Alloc<T>(x_grad);
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if (x_grad->numel() == 0) return;
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Copy(dev_ctx, out_grad, dev_ctx.GetPlace(), false, x_grad);
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auto dx_dims = x_grad->dims();
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auto strides = funcs::CalStride(dx_dims);
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auto size = x_grad->numel();
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auto wrapsize = std::min(size, dx_dims[1] * dx_dims[1]);
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// The wrap mode supported only the dims equals to 2; In wrap mode, the
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// value will be filled in cycles
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if (wrap) {
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wrapsize = size;
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}
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for (int64_t i = 0; i < wrapsize; i += strides) {
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if (i % dx_dims[1] + offset >= 0 &&
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i % dx_dims[1] + offset < dx_dims[1]) {
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data[i + offset] = T(0);
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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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PD_REGISTER_KERNEL(fill_diagonal_grad,
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CPU,
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ALL_LAYOUT,
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phi::FillDiagonalGradKernel,
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float,
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double,
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int64_t,
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int,
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phi::float16,
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bool) {}
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