1 // Copyright (C) 2018-2019 Intel Corporation
2 // SPDX-License-Identifier: Apache-2.0
7 #include <description_buffer.hpp>
8 #include "ie_built_in_impl.hpp"
15 namespace InferenceEngine {
16 namespace ShapeInfer {
19 *@brief Implementation of Shape inference for PriorBox layer
21 class PriorBoxShapeProp : public BuiltInShapeInferImpl {
23 explicit PriorBoxShapeProp(const std::string& type) : BuiltInShapeInferImpl(type) {}
25 void inferShapesImpl(const std::vector<Blob::CPtr>& inBlobs,
26 const std::map<std::string, std::string>& params,
27 const std::map<std::string, Blob::Ptr>& blobs,
28 std::vector<SizeVector>& outShapes) override {
30 CNNLayer cnnLayer(lp);
31 cnnLayer.params = params;
32 cnnLayer.type = _type;
33 validate(&cnnLayer, inBlobs, params, blobs);
34 std::vector<float> min_sizes = cnnLayer.GetParamAsFloats("min_size", {});
35 std::vector<float> max_sizes = cnnLayer.GetParamAsFloats("max_size", {});
36 bool flip = static_cast<bool>(cnnLayer.GetParamAsInt("flip"));
37 const std::vector<float> aspect_ratios = cnnLayer.GetParamAsFloats("aspect_ratio", {});
38 size_t num_priors = 0;
40 bool scale_all_sizes = static_cast<bool>(cnnLayer.GetParamAsInt("scale_all_sizes", 1));
42 if (scale_all_sizes) {
43 num_priors = ((flip ? 2 : 1) * aspect_ratios.size() + 1) * min_sizes.size() + max_sizes.size();
45 num_priors = (flip ? 2 : 1) * aspect_ratios.size() + min_sizes.size() - 1;
48 size_t res_prod = num_priors * 4;
49 for (int i = 2; i < inShapes[0].size(); i++)
50 res_prod *= inShapes[0][i];
51 outShapes.push_back({1, 2, res_prod});
55 } // namespace ShapeInfer
56 } // namespace InferenceEngine