// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #pragma once #include "paddle/phi/core/dense_tensor.h" namespace phi { template void PriorBoxKernel(const Context& ctx, const DenseTensor& input, const DenseTensor& image, const std::vector& min_sizes, const std::vector& aspect_ratios, const std::vector& variances, const std::vector& max_sizes, bool flip, bool clip, float step_w, float step_h, float offset, bool min_max_aspect_ratios_order, DenseTensor* out, DenseTensor* var); inline void ExpandAspectRatios(const std::vector& input_aspect_ratior, bool flip, std::vector* output_aspect_ratior) { constexpr float epsilon = 1e-6; output_aspect_ratior->clear(); output_aspect_ratior->push_back(1.0f); for (size_t i = 0; i < input_aspect_ratior.size(); ++i) { float ar = input_aspect_ratior[i]; bool already_exist = false; for (size_t j = 0; j < output_aspect_ratior->size(); ++j) { if (fabs(ar - output_aspect_ratior->at(j)) < epsilon) { already_exist = true; break; } } if (!already_exist) { output_aspect_ratior->push_back(ar); if (flip) { output_aspect_ratior->push_back(1.0f / ar); } } } } } // namespace phi