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//
// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ConvertFp32ToBf16TestImpl.hpp"
#include <armnnTestUtils/TensorCopyUtils.hpp>
#include <armnnTestUtils/WorkloadTestUtils.hpp>
#include <TensorHelpers.hpp>
LayerTestResult<armnn::BFloat16, 4> ConvertFp32ToBf16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory)
{
IgnoreUnused(memoryManager);
const armnn::TensorInfo inputTensorInfo({1, 2, 4, 3}, armnn::DataType::Float32);
const armnn::TensorInfo outputTensorInfo({1, 2, 4, 3}, armnn::DataType::BFloat16);
std::vector<float> input =
{
-37.5f, -15.2f, -8.76f,
-2.0f, -1.5f, -1.3f,
-0.5f, -0.4f, 0.0f,
1.0f, 0.4f, 0.5f,
1.3f, 1.5f, 2.0f,
8.76f, 15.2f, 37.5f,
3.8f, // 0x40733333 Round down
3.1055E+29f, // 0x707ADC3C Round up
9.149516E-10f, // 0x307B7FFF Round down
-3.8f, // 0xC0733333 Round down
-3.1055E+29f, // 0xF07ADC3C Round up
-9.149516E-10f // 0xB07B7FFF Round down
};
std::vector<armnn::BFloat16> expectedOutput = armnnUtils::QuantizedVector<armnn::BFloat16>(
{
-37.5f, -15.2f, -8.76f,
-2.0f, -1.5f, -1.3f,
-0.5f, -0.4f, 0.0f,
1.0f, 0.4f, 0.5f,
1.3f, 1.5f, 2.0f,
8.76f, 15.2f, 37.5f,
3.796875f, // 0x4073
3.1072295E29f, // 0x707B
9.131327E-10f, // 0x307B
-3.796875f, // 0xC073
-3.1072295E29f, // 0xF07B
-9.131327E-10f // 0xB07B
},
1.0f, 0);
std::vector<armnn::BFloat16> actualOutput(outputTensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
armnn::ConvertFp32ToBf16QueueDescriptor data;
armnn::WorkloadInfo info;
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::ConvertFp32ToBf16,
data,
info);
inputHandle->Allocate();
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle.get(), input.data());
workload->Execute();
CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
return LayerTestResult<armnn::BFloat16, 4>(actualOutput,
expectedOutput,
outputHandle->GetShape(),
outputTensorInfo.GetShape());
}
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