wehub-resource-sync
60 lines
2.0 KiB
C++
60 lines
2.0 KiB
C++
// Copyright (c) 2023 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/transpose_kernel.h"
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#include "paddle/common/flags.h"
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#include "paddle/phi/backends/all_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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COMMON_DECLARE_bool(use_stride_kernel);
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namespace phi {
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template <typename Context>
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void TransposeStridedKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const std::vector<int>& axis,
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DenseTensor* out) {
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if (!FLAGS_use_stride_kernel) {
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PADDLE_THROW(common::errors::Fatal(
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"FLAGS_use_stride_kernel is closed. Strided kernel "
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"be called, something wrong has happened!"));
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}
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size_t x_rank = x.dims().size();
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std::vector<int> formatted_axis = axis;
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for (size_t i = 0; i < axis.size(); i++) {
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if (axis[i] < 0) {
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formatted_axis[i] = static_cast<int>(axis[i] + x_rank);
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}
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}
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auto meta = out->meta();
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auto in_stride = x.strides();
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meta.strides = in_stride;
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for (int i = 0; i < static_cast<int>(formatted_axis.size()); i++) {
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meta.strides[i] = in_stride[formatted_axis[i]];
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}
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meta.offset = x.offset();
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out->set_meta(meta);
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out->ResetHolder(x.Holder());
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out->ShareInplaceVersionCounterWith(x);
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}
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} // namespace phi
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PD_REGISTER_KERNEL_FOR_ALL_BACKEND_DTYPE(transpose,
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STRIDED,
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phi::TransposeStridedKernel) {}
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