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//
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "FakeQuantizationTestImpl.hpp"
#include <armnn/backends/TensorHandle.hpp>
#include <armnnTestUtils/TensorCopyUtils.hpp>
#include <armnnTestUtils/WorkloadTestUtils.hpp>
#include <TensorHelpers.hpp>
LayerTestResult<float, 2> FakeQuantizationTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory)
{
IgnoreUnused(memoryManager);
constexpr unsigned int width = 2;
constexpr unsigned int height = 3;
const armnn::TensorInfo tensorInfo({ height, width }, armnn::DataType::Float32);
std::vector<float> input =
{
-10.0f, -5.0f,
0.0f, 5.0f,
10.0f, 10.0f
};
std::vector<float> actualOutput(tensorInfo.GetNumElements());
std::vector<float> expectedOutput(tensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(tensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(tensorInfo);
armnn::FakeQuantizationQueueDescriptor data;
armnn::WorkloadInfo info;
AddInputToWorkload(data, info, tensorInfo, inputHandle.get());
AddOutputToWorkload(data, info, tensorInfo, outputHandle.get());
float min = -10.f;
float max = 10.f;
data.m_Parameters.m_Min = min;
data.m_Parameters.m_Max = max;
armnn::PassthroughTensorHandle refHandle(tensorInfo, expectedOutput.data());
armnn::FakeQuantizationQueueDescriptor refData = data;
armnn::WorkloadInfo refInfo = info;
SetWorkloadOutput(refData, refInfo, 0, tensorInfo, &refHandle);
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::FakeQuantization,
data,
info);
inputHandle->Allocate();
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle.get(), input.data());
workload->PostAllocationConfigure();
workload->Execute();
CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
expectedOutput =
{
0.0f, 63.0f,
128.0f, 191.0f,
255.0f, 255.0f
};
return LayerTestResult<float, 2>(actualOutput,
expectedOutput,
outputHandle->GetShape(),
tensorInfo.GetShape());
}
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