wehub-resource-sync
62 lines
1.9 KiB
C++
62 lines
1.9 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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#pragma once
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#include <algorithm>
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#include <string>
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#include <vector>
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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namespace phi {
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template <typename T, typename Context>
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void PixelShuffleKernel(const Context& dev_ctx,
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const DenseTensor& x,
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int upscale_factor,
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const std::string& data_format,
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DenseTensor* out) {
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auto* in = &x;
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dev_ctx.template Alloc<T>(out);
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if (out && out->numel() == 0) {
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return;
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}
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int factor = upscale_factor;
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bool channel_last = (data_format == "NHWC");
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const auto& in_dims = in->dims();
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const auto& o_dims = out->dims();
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DenseTensor t(*in);
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if (!channel_last) {
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t.Resize({in_dims[0], o_dims[1], factor, factor, in_dims[2], in_dims[3]});
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} else {
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t.Resize({in_dims[0], in_dims[1], in_dims[2], o_dims[3], factor, factor});
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}
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std::vector<int> axis = {0, 1, 4, 2, 5, 3};
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DenseTensor o(*out);
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if (!channel_last) {
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o.Resize({in_dims[0], o_dims[1], in_dims[2], factor, in_dims[3], factor});
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} else {
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o.Resize({in_dims[0], in_dims[1], factor, in_dims[2], factor, o_dims[3]});
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}
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funcs::Transpose<Context, T, 6> trans;
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trans(dev_ctx, t, &o, axis);
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out->Resize(o_dims);
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}
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} // namespace phi
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