inference-engine/src/inference_engine/shape_infer/built-in/ie_resample_shape_infer.hpp

   1 // Copyright (C) 2018-2019 Intel Corporation
   2 // SPDX-License-Identifier: Apache-2.0
   3 //
   4
   5 #pragma once
   6
   7 #include <description_buffer.hpp>
   8 #include "ie_built_in_impl.hpp"
   9 #include <ie_layers.h>
  10 #include <map>
  11 #include <memory>
  12 #include <string>
  13 #include <vector>
  14
  15 namespace InferenceEngine {
  16 namespace ShapeInfer {
  17
  18 /**
  19  *@brief Implementation of Shape inference for Resample layer
  20  */
  21 class ResampleShapeProp : public BuiltInShapeInferImpl {
  22 public:
  23     explicit ResampleShapeProp(const std::string& type) : BuiltInShapeInferImpl(type) {}
  24
  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 {
  29         LayerParams lp{};
  30         CNNLayer cnnLayer(lp);
  31         cnnLayer.params = params;
  32         cnnLayer.type = _type;
  33         validate(&cnnLayer, inBlobs, params, blobs);
  34         SizeVector outShape;
  35         if (inBlobs.size() == 2) {
  36             auto* buffer = inBlobs[1]->cbuffer().as<float*>();
  37             if (buffer != nullptr) {
  38                 for (int i = 0; i < inBlobs[1]->size(); i++) {
  39                     outShape.push_back(static_cast<unsigned long>(buffer[i]));
  40                 }
  41             } else {
  42                 THROW_IE_EXCEPTION << "Second input must have allocated data";
  43             }
  44         } else {
  45             auto scale = static_cast<size_t>(cnnLayer.GetParamAsInt("factor"));
  46             outShape = {inShapes[0][0], inShapes[0][1]};
  47             for (int i = 2; i < inShapes[0].size(); i++)
  48                 outShape.push_back(inShapes[0][i] * scale);
  49         }
  50         outShapes.push_back(outShape);
  51     }
  52 };
  53
  54 }  // namespace ShapeInfer
  55 }  // namespace InferenceEngine