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-rw-r--r--src/backends/backendsCommon/test/layerTests/CastTestImpl.cpp229
1 files changed, 229 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/CastTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/CastTestImpl.cpp
new file mode 100644
index 0000000000..ad23b8c767
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/CastTestImpl.cpp
@@ -0,0 +1,229 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "CastTestImpl.hpp"
+#include "ElementwiseUnaryTestImpl.hpp"
+
+
+template<armnn::DataType inputDataType, armnn::DataType outputDataType, typename TInput, typename TOutput>
+LayerTestResult<TOutput, 4> CastTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const std::vector<TInput>& inputValues,
+ const std::vector<TOutput>& outputValues)
+{
+ IgnoreUnused(memoryManager);
+ armnn::TensorInfo inputTensorInfo({1, 3, 2, 3}, inputDataType);
+ armnn::TensorInfo outputTensorInfo({1, 3, 2, 3}, outputDataType);
+ float quantizationScale = 1.0f;
+ int32_t quantizationOffset = 0;
+
+ if(armnn::IsQuantizedType<TInput>())
+ {
+ inputTensorInfo.SetQuantizationScale(quantizationScale);
+ inputTensorInfo.SetQuantizationOffset(quantizationOffset);
+ }
+ if(armnn::IsQuantizedType<TOutput>())
+ {
+ outputTensorInfo.SetQuantizationScale(quantizationScale);
+ outputTensorInfo.SetQuantizationOffset(quantizationOffset);
+ }
+
+ auto input = MakeTensor<TInput, 4>(inputTensorInfo, inputValues);
+
+ LayerTestResult<TOutput, 4> ret(outputTensorInfo);
+ ret.outputExpected = MakeTensor<TOutput, 4>(outputTensorInfo, outputValues);
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::CastQueueDescriptor data;
+ armnn::WorkloadInfo info;
+ AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateCast(data, info);
+
+ inputHandle->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
+
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get());
+
+ return ret;
+}
+
+LayerTestResult<float, 4> CastInt32ToFloat2dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<int32_t> inputValues = { -1, -3, -1, -3, -1, -3, -1, -3, 1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ std::vector<float> outputValues = { -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, 1.0f,
+ 3.0f, 1.0f, 3.0f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ return CastTest<armnn::DataType::Signed32, armnn::DataType::Float32>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<float, 4> CastInt16ToFloat2dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<int16_t> inputValues = { -1, -3, -1, -3, -1, -3, -1, -3, 1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ std::vector<float> outputValues = { -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, 1.0f,
+ 3.0f, 1.0f, 3.0f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ return CastTest<armnn::DataType::QSymmS16, armnn::DataType::Float32>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<float, 4> CastInt8ToFloat2dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<int8_t> inputValues = { -1, -3, -1, -3, -1, -3, -1, -3, 1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ std::vector<float> outputValues = { -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, 1.0f,
+ 3.0f, 1.0f, 3.0f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ return CastTest<armnn::DataType::QSymmS8, armnn::DataType::Float32>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<float, 4> CastInt8AsymmToFloat2dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<int8_t> inputValues = { -1, -3, -1, -3, -1, -3, -1, -3, 1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ std::vector<float> outputValues = { -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, 1.0f,
+ 3.0f, 1.0f, 3.0f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ return CastTest<armnn::DataType::QAsymmS8, armnn::DataType::Float32>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues, outputValues);
+}
+
+LayerTestResult<float, 4> CastUInt8ToFloat2dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<u_int8_t> inputValues = { 1, 3, 1, 3, 1, 3, 1, 3, 1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ std::vector<float> outputValues = { 1.0f, 3.0f, 1.0f, 3.0f, 1.0f, 3.0f, 1.0f, 3.0f, 1.0f,
+ 3.0f, 1.0f, 3.0f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ return CastTest<armnn::DataType::QAsymmU8, armnn::DataType::Float32>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<uint8_t, 4> CastInt8ToUInt82dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<int8_t> inputValues = { -1, -3, -1, -3, -1, -3, -1, -3, -1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ std::vector<uint8_t> outputValues = { 0, 0, 0, 0, 0, 0, 0, 0, 0,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ return CastTest<armnn::DataType::QSymmS8, armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<uint8_t, 4> CastInt8AsymmToUInt82dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<int8_t> inputValues = { -1, -3, -1, -3, -1, -3, -1, -3, -1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ std::vector<uint8_t> outputValues = { 0, 0, 0, 0, 0, 0, 0, 0, 0,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ return CastTest<armnn::DataType::QAsymmS8, armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<float, 4> CastFloat16ToFloat322dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ using namespace half_float::literal;
+
+ std::vector<armnn::Half> inputValues = { -1.10_h, -3._h, -1.30_h, -3._h, -1._h, -3._h, -1._h, -3._h, 1._h,
+ 3.10_h, 1._h, 3.30_h, 1._h, 2._h, 1._h, 3._h, 1._h, 3._h };
+ std::vector<float> outputValues = { -1.1f, -3.0f, -1.3f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, 1.0f,
+ 3.1f, 1.0f, 3.3f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ return CastTest<armnn::DataType::Float16, armnn::DataType::Float32>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<float, 4> CastBFloat16ToFloat322dTest(armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+
+ std::vector<armnn::BFloat16> inputValues = 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
+ },
+ 1.0f, 0);
+
+
+ std::vector<float> outputValues = { -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 };
+
+ return CastTest<armnn::DataType::BFloat16, armnn::DataType::Float32>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues, outputValues);
+}
+
+LayerTestResult<armnn::Half, 4> CastFloat32ToFloat162dTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ using namespace half_float::literal;
+
+ std::vector<float> inputValues = { -37.5f, -15.2f, -8.76f, -2.0f, -1.5f, -1.3f, -0.5f, -0.4f,
+ 0.00000004f, 3.4E38f, 300.0f, 0.5f, 1.3f, 1.5f, 2.1E4f, 8.76f, 15.2f, 37.5f };
+ std::vector<armnn::Half> outputValues = {-37.50_h, -15.20_h, -8.76_h, -2._h, -1.50_h, -1.30_h, -0.50_h, -0.40_h,
+ 0._h, 6.55E4_h, 300._h, 0.50_h, 1.30_h, 1.50_h, 2.1E4_h, 8.76_h, 15.20_h, 37.50_h};
+
+ return CastTest<armnn::DataType::Float32, armnn::DataType::Float16>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<int8_t , 4> CastFloat32ToInt82dTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<float> inputValues = { -1.0f, -3.5f, -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, 1.0f,
+ 3.1f, 1.5f, 3.9f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ std::vector<int8_t> outputValues = { -1, -3, -1, -3, -1, -3, -1, -3, 1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ return CastTest<armnn::DataType::Float32, armnn::DataType::QAsymmS8>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
+
+LayerTestResult<uint8_t , 4> CastFloat32ToUInt82dTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+ std::vector<float> inputValues = { -1.0f, -3.5f, -1.0f, -3.0f, -1.0f, -3.0f, -1.0f, -3.0f, 1.0f,
+ 3.1f, 1.5f, 3.9f, 1.0f, 2.0f, 1.0f, 3.0f, 1.0f, 3.0f };
+ std::vector<uint8_t> outputValues = { 0, 0, 0, 0, 0, 0, 0, 0, 1,
+ 3, 1, 3, 1, 2, 1, 3, 1, 3 };
+ return CastTest<armnn::DataType::Float32, armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,
+ tensorHandleFactory, inputValues,
+ outputValues);
+}
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-26 02:23:41 +0000