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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <ResolveType.hpp>
#include <armnn/INetwork.hpp>
#include <backendsCommon/test/CommonTestUtils.hpp>
#include <doctest/doctest.h>
#include <vector>
namespace
{
template<typename armnn::DataType DataType>
INetworkPtr CreateBatchToSpaceNdNetwork(const armnn::TensorShape& inputShape,
const armnn::TensorShape& outputShape,
std::vector<unsigned int>& blockShape,
std::vector<std::pair<unsigned int, unsigned int>>& crops,
armnn::DataLayout dataLayout,
const float qScale = 1.0f,
const int32_t qOffset = 0)
{
using namespace armnn;
// Builds up the structure of the network.
INetworkPtr net(INetwork::Create());
TensorInfo inputTensorInfo(inputShape, DataType, qScale, qOffset, true);
TensorInfo outputTensorInfo(outputShape, DataType, qScale, qOffset);
BatchToSpaceNdDescriptor batchToSpaceNdDesc(blockShape, crops);
batchToSpaceNdDesc.m_DataLayout = dataLayout;
IConnectableLayer* batchToSpaceNd = net->AddBatchToSpaceNdLayer(batchToSpaceNdDesc, "batchToSpaceNd");
IConnectableLayer* input = net->AddInputLayer(0, "input");
IConnectableLayer* output = net->AddOutputLayer(0, "output");
Connect(batchToSpaceNd, output, outputTensorInfo, 0, 0);
Connect(input, batchToSpaceNd, inputTensorInfo, 0, 0);
return net;
}
template<armnn::DataType ArmnnType>
void BatchToSpaceNdEndToEnd(const std::vector<BackendId>& backends, armnn::DataLayout dataLayout)
{
using namespace armnn;
using T = ResolveType<ArmnnType>;
std::vector<unsigned int> blockShape {2, 2};
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
const TensorShape& inputShape = { 4, 1, 1, 1 };
const TensorShape& outputShape = (dataLayout == DataLayout::NCHW)
? std::initializer_list<unsigned int>({ 1, 1, 2, 2 })
: std::initializer_list<unsigned int>({ 1, 2, 2, 1 });
// Builds up the structure of the network
INetworkPtr net = CreateBatchToSpaceNdNetwork<ArmnnType>(inputShape, outputShape, blockShape, crops, dataLayout);
CHECK(net);
// Creates structures for input & output.
std::vector<T> inputData{ 1, 2, 3, 4 };
std::vector<T> expectedOutput{ 1, 2, 3, 4 };
std::map<int, std::vector<T>> inputTensorData = { { 0, inputData } };
std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
}
template<armnn::DataType ArmnnType>
void BatchToSpaceNdComplexEndToEnd(const std::vector<BackendId>& backends, armnn::DataLayout dataLayout)
{
using namespace armnn;
using T = ResolveType<ArmnnType>;
std::vector<unsigned int> blockShape {2, 2};
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};
const TensorShape& inputShape = (dataLayout == DataLayout::NCHW)
? std::initializer_list<unsigned int>({ 8, 1, 1, 3 })
: std::initializer_list<unsigned int>({ 8, 1, 3, 1 });
const TensorShape& outputShape = (dataLayout == DataLayout::NCHW)
? std::initializer_list<unsigned int>({ 2, 1, 2, 4 })
: std::initializer_list<unsigned int>({ 2, 2, 4, 1 });
// Builds up the structure of the network
INetworkPtr net = CreateBatchToSpaceNdNetwork<ArmnnType>(inputShape, outputShape, blockShape, crops, dataLayout);
CHECK(net);
// Creates structures for input & output.
std::vector<T> inputData{
0, 1, 3, 0, 9, 11,
0, 2, 4, 0, 10, 12,
0, 5, 7, 0, 13, 15,
0, 6, 8, 0, 14, 16
};
std::vector<T> expectedOutput{
1, 2, 3, 4,
5, 6, 7, 8,
9, 10, 11, 12,
13, 14, 15, 16
};
std::map<int, std::vector<T>> inputTensorData = { { 0, inputData } };
std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
}
} // anonymous namespace
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