IVGCVSW-3381 Break up LayerTests.hpp into more manageable files
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Icf39434f09fd340ad664cb3b97b8bee6d9da4838
diff --git a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
new file mode 100644
index 0000000..c3cacd5
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
@@ -0,0 +1,154 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ConstantTestImpl.hpp"
+
+#include <Permute.hpp>
+#include <ResolveType.hpp>
+
+#include <armnn/ArmNN.hpp>
+
+#include <backendsCommon/CpuTensorHandle.hpp>
+
+#include <backendsCommon/test/TensorCopyUtils.hpp>
+#include <backendsCommon/test/WorkloadTestUtils.hpp>
+
+#include <test/TensorHelpers.hpp>
+
+namespace
+{
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> ConstantTestImpl(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float qScale,
+ int32_t qOffset)
+{
+ constexpr unsigned int inputWidth = 3;
+ constexpr unsigned int inputHeight = 4;
+ constexpr unsigned int inputChannels = 3;
+ constexpr unsigned int inputBatchSize = 2;
+
+ constexpr unsigned int outputWidth = inputWidth;
+ constexpr unsigned int outputHeight = inputHeight;
+ constexpr unsigned int outputChannels = inputChannels;
+ constexpr unsigned int outputBatchSize = inputBatchSize;
+
+ armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth },
+ ArmnnType, qScale, qOffset);
+
+ armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth },
+ ArmnnType, qScale, qOffset);
+
+ // Set quantization parameters if the requested type is a quantized type.
+ if(armnn::IsQuantizedType<T>())
+ {
+ inputTensorInfo.SetQuantizationScale(qScale);
+ inputTensorInfo.SetQuantizationOffset(qOffset);
+ outputTensorInfo.SetQuantizationScale(qScale);
+ outputTensorInfo.SetQuantizationOffset(qOffset);
+ }
+
+ auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>(
+ QuantizedVector<T>(qScale, qOffset, {
+ // Batch 0, Channel 0
+ 235.0f, 46.0f, 178.0f,
+ 100.0f, 123.0f, 19.0f,
+ 172.0f, 74.0f, 250.0f,
+ 6.0f, 195.0f, 80.0f,
+
+ // Batch 0, Channel 1
+ 113.0f, 95.0f, 202.0f,
+ 77.0f, 114.0f, 71.0f,
+ 122.0f, 246.0f, 166.0f,
+ 82.0f, 28.0f, 37.0f,
+
+ // Batch 0, Channel 2
+ 56.0f, 170.0f, 162.0f,
+ 194.0f, 89.0f, 254.0f,
+ 12.0f, 209.0f, 200.0f,
+ 1.0f, 64.0f, 54.0f,
+
+ // Batch 1, Channel 0
+ 67.0f, 90.0f, 49.0f,
+ 7.0f, 163.0f, 18.0f,
+ 25.0f, 117.0f, 103.0f,
+ 247.0f, 59.0f, 189.0f,
+
+ // Batch 1, Channel 1
+ 239.0f, 104.0f, 199.0f,
+ 17.0f, 124.0f, 153.0f,
+ 222.0f, 217.0f, 75.0f,
+ 32.0f, 126.0f, 21.0f,
+
+ // Batch 1, Channel 2
+ 97.0f, 145.0f, 215.0f,
+ 115.0f, 116.0f, 238.0f,
+ 226.0f, 16.0f, 132.0f,
+ 92.0f, 125.0f, 88.0f,
+ })));
+
+ LayerTestResult<T, 4> result(outputTensorInfo);
+ result.outputExpected = input;
+
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::ScopedCpuTensorHandle constantTensor(inputTensorInfo);
+ AllocateAndCopyDataToITensorHandle(&constantTensor, &input[0][0][0][0]);
+
+ armnn::ConstantQueueDescriptor descriptor;
+ descriptor.m_LayerOutput = &constantTensor;
+
+ armnn::WorkloadInfo info;
+ AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConstant(descriptor, info);
+
+ outputHandle->Allocate();
+
+ workload->PostAllocationConfigure();
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
+ return result;
+}
+
+} // anonymous namespace
+
+LayerTestResult<float, 4> ConstantTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ return ConstantTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0);
+}
+
+LayerTestResult<int16_t, 4> ConstantInt16SimpleQuantizationScaleNoOffsetTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ return ConstantTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 1.0f, 0);
+}
+
+LayerTestResult<uint8_t, 4> ConstantUint8SimpleQuantizationScaleNoOffsetTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ return ConstantTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 1.0f, 0);
+}
+
+LayerTestResult<uint8_t, 4> ConstantUint8CustomQuantizationScaleAndOffsetTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ return ConstantTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 2e-6f, 1);
+}
+
+LayerTestResult<int16_t, 4> ConstantInt16CustomQuantizationScaleAndOffsetTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ return ConstantTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 2e-6f, 1);
+}