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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "CommonTestUtils.hpp"
#include <armnn/INetwork.hpp>
#include <ResolveType.hpp>
#include <doctest/doctest.h>
namespace
{
template<typename T>
armnn::INetworkPtr CreateDequantizeNetwork(const armnn::TensorInfo& inputInfo,
const armnn::TensorInfo& outputInfo)
{
armnn::INetworkPtr net(armnn::INetwork::Create());
armnn::IConnectableLayer* inputLayer = net->AddInputLayer(0);
armnn::IConnectableLayer* dequantizeLayer = net->AddDequantizeLayer("Dequantize");
armnn::IConnectableLayer* outputLayer = net->AddOutputLayer(0, "output");
Connect(inputLayer, dequantizeLayer, inputInfo, 0, 0);
Connect(dequantizeLayer, outputLayer, outputInfo, 0, 0);
return net;
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void DequantizeEndToEndLayerTestImpl(const std::vector<BackendId>& backends,
const armnn::TensorShape& tensorShape,
const std::vector<T>& input,
const std::vector<float>& expectedOutput,
float scale,
int32_t offset)
{
armnn::TensorInfo inputInfo(tensorShape, ArmnnType);
armnn::TensorInfo outputInfo(tensorShape, armnn::DataType::Float32);
inputInfo.SetQuantizationScale(scale);
inputInfo.SetQuantizationOffset(offset);
inputInfo.SetConstant(true);
// Builds up the structure of the network
armnn::INetworkPtr net = CreateDequantizeNetwork<T>(inputInfo, outputInfo);
CHECK(net);
std::map<int, std::vector<T>> inputTensorData = { { 0, input } };
std::map<int, std::vector<float>> expectedOutputData = { { 0, expectedOutput } };
EndToEndLayerTestImpl<ArmnnType, armnn::DataType::Float32>(
move(net), inputTensorData, expectedOutputData, backends);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void DequantizeEndToEndSimple(const std::vector<BackendId>& backends)
{
const armnn::TensorShape tensorShape({ 1, 2, 2, 4 });
std::vector<T> inputData = std::vector<T>(
{
2, 4, 6, 8,
10, 12, 14, 16,
18, 20, 22, 24,
26, 28, 30, 32
});
std::vector<float> expectedOutputData = std::vector<float>(
{
1.0f, 2.0f, 3.0f, 4.0f,
5.0f, 6.0f, 7.0f, 8.0f,
9.0f, 10.0f, 11.0f, 12.0f,
13.0f, 14.0f, 15.0f, 16.0f
});
DequantizeEndToEndLayerTestImpl<ArmnnType>(backends, tensorShape, inputData, expectedOutputData, 0.5f, 0);
};
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void DequantizeEndToEndOffset(const std::vector<BackendId>& backends)
{
const armnn::TensorShape tensorShape({ 1, 2, 2, 4 });
std::vector<T> inputData = std::vector<T>(
{
3, 5, 7, 9,
11, 13, 15, 17,
19, 21, 23, 25,
27, 29, 31, 33
});
std::vector<float> expectedOutputData = std::vector<float>(
{
1.0f, 2.0f, 3.0f, 4.0f,
5.0f, 6.0f, 7.0f, 8.0f,
9.0f, 10.0f, 11.0f, 12.0f,
13.0f, 14.0f, 15.0f, 16.0f
});
DequantizeEndToEndLayerTestImpl<ArmnnType>(backends, tensorShape, inputData, expectedOutputData, 0.5f, 1);
};
} // anonymous namespace
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