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// Copyright (C) 2018 Intel Corporation
//
// SPDX-License-Identifier: Apache-2.0
//
#pragma once
#include <description_buffer.hpp>
#include "ie_built_in_impl.hpp"
#include <map>
#include <memory>
#include <string>
#include <vector>
#include <v2_format_parser.h>
namespace InferenceEngine {
namespace ShapeInfer {
/**
*@brief Implementation of Shape inference for Deconvolution layer
*/
class DeconvShapeProp : public BuiltInShapeInferImpl {
public:
explicit DeconvShapeProp(const std::string& type) : BuiltInShapeInferImpl(type) {}
void inferShapesImpl(const std::vector<SizeVector>& inShapes,
const std::map<std::string, std::string>& params,
const std::map<std::string, Blob::Ptr>& blobs,
std::vector<SizeVector>& outShapes) override {
LayerParams lp{};
DeconvolutionLayer deconvLayer(lp);
deconvLayer.params = params;
deconvLayer.type = _type;
validate(&deconvLayer, inShapes, params, blobs);
auto dims = inShapes[0];
size_t inputN = dims[0];
size_t IH = dims[2];
size_t IW = dims[3];
int PR = -1, PB = -1;
float OHTemp, OWTemp, KH, KW;
if (deconvLayer._dilation[Y_AXIS])
KH = (deconvLayer._kernel[Y_AXIS] - 1) * deconvLayer._dilation[Y_AXIS] + 1;
else
KH = deconvLayer._kernel[Y_AXIS];
if (deconvLayer._dilation[X_AXIS])
KW = (deconvLayer._kernel[X_AXIS] - 1) * deconvLayer._dilation[X_AXIS] + 1;
else
KW = deconvLayer._kernel[X_AXIS];
size_t SH = deconvLayer._stride[Y_AXIS];
size_t SW = deconvLayer._stride[X_AXIS];
size_t PH = deconvLayer._padding[Y_AXIS];
size_t PW = deconvLayer._padding[X_AXIS];
size_t OC = deconvLayer._out_depth;
auto it = deconvLayer.params.find("auto_pad");
std::string padType;
if (it != deconvLayer.params.end()) padType = it->second;
if (padType == "valid") {
OHTemp = IH * SH + KH - 1;
OWTemp = IW * SW + KW - 1;
} else if ((padType == "same_upper") || (padType == "same_lower")) {
OHTemp = IH * SH;
OWTemp = IW * SW;
} else {
auto ir_version = details::BaseCreator::version_;
bool isEndPaddingsSet = false;
try {
if (ir_version == 3) {
auto pads_end = deconvLayer.GetParamAsUInts("pads_end");
PR = pads_end[pads_end.size() - 1 - X_AXIS];
PB = pads_end[pads_end.size() - 1 - Y_AXIS];
} else if (ir_version < 3) {
PR = deconvLayer.GetParamAsInt("pad-r");
PB = deconvLayer.GetParamAsInt("pad-b");
}
isEndPaddingsSet = true;
} catch (...) {}
if (!isEndPaddingsSet) {
OHTemp = SH * (IH - 1) + KH - 2 * PH;
OWTemp = SW * (IW - 1) + KW - 2 * PW;
} else {
OHTemp = SH * (IH - 1) + KH - PH - PB;
OWTemp = SW * (IW - 1) + KW - PW - PR;
}
}
if (OHTemp < 0 || OWTemp < 0)
THROW_IE_EXCEPTION << "New shapes " << details::dumpVec(dims) << " make output shape negative";
size_t OH = static_cast<size_t>(OHTemp);
size_t OW = static_cast<size_t>(OWTemp);
outShapes.emplace_back(std::initializer_list<size_t>{inputN, OC, OH, OW});
}
};
} // namespace ShapeInfer
} // namespace InferenceEngine
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