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Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/BatchMatMulTestImpl.cpp')
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/BatchMatMulTestImpl.cpp | 1010 |
1 files changed, 1010 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/BatchMatMulTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/BatchMatMulTestImpl.cpp new file mode 100644 index 0000000000..41add6e6da --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/BatchMatMulTestImpl.cpp @@ -0,0 +1,1010 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "BatchMatMulTestImpl.hpp" + +#include <armnn/backends/IBackendInternal.hpp> +#include <armnn/backends/Workload.hpp> +#include <armnn/backends/WorkloadData.hpp> +#include <armnn/backends/WorkloadFactory.hpp> + +#include <armnnTestUtils/WorkloadTestUtils.hpp> +#include <armnnUtils/QuantizeHelper.hpp> +#include <armnnTestUtils/TensorCopyUtils.hpp> +#include <armnn/Optional.hpp> + + +template<armnn::DataType ArmnnType, typename T, std::size_t NumDims> +LayerTestResult<T, NumDims> BatchMatMulTestImpl( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory, + armnn::BatchMatMulDescriptor descriptor, + const std::vector<T>& inputX, + const std::vector<T>& inputY, + const std::vector<T>& outputExpected, + const armnn::TensorInfo& inputXInfo, + const armnn::TensorInfo& inputYInfo, + const armnn::TensorInfo& outputInfo) +{ + std::vector<T> outputActual(outputInfo.GetNumElements()); + + std::unique_ptr<armnn::ITensorHandle> inputXHandle = tensorHandleFactory.CreateTensorHandle(inputXInfo); + std::unique_ptr<armnn::ITensorHandle> inputYHandle = tensorHandleFactory.CreateTensorHandle(inputYInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); + + armnn::BatchMatMulQueueDescriptor queueDescriptor; + queueDescriptor.m_Parameters = descriptor; + armnn::WorkloadInfo workloadInfo; + + AddInputToWorkload(queueDescriptor, workloadInfo, inputXInfo, inputXHandle.get()); + AddInputToWorkload(queueDescriptor, workloadInfo, inputYInfo, inputYHandle.get()); + AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get()); + + auto workload = workloadFactory.CreateWorkload(armnn::LayerType::BatchMatMul, queueDescriptor, workloadInfo); + + inputXHandle->Allocate(); + inputYHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputXHandle.get(), inputX.data()); + CopyDataToITensorHandle(inputYHandle.get(), inputY.data()); + + workload->PostAllocationConfigure(); + ExecuteWorkload(*workload, memoryManager); + + CopyDataFromITensorHandle(outputActual.data(), outputHandle.get()); + + return LayerTestResult<T, NumDims>(outputActual, + outputExpected, + outputHandle->GetShape(), + outputInfo.GetShape()); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 2> BatchMatMul2DSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor(); // Arbitrary layout with no transpose/adjointing + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({2,2}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 2, + 3, 4 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 5, 6, + 7, 8 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 19, 22, + 43, 50 + }, qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 2>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 2> +BatchMatMul2DSimpleTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 2> +BatchMatMul2DSimpleTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 2> +BatchMatMul2DSimpleTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 2> +BatchMatMul2DSimpleTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 2> +BatchMatMul2DSimpleTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 2> +BatchMatMul2DSimpleTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 3> BatchMatMul3DSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor(); // Arbitrary layout with no transpose/adjointing + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({1,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({1,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({1,2,2}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 2, + 3, 4 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 5, 6, + 7, 8 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 19, 22, + 43, 50 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 3>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 3> +BatchMatMul3DSimpleTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 3> +BatchMatMul3DSimpleTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 3> +BatchMatMul3DSimpleTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 3> +BatchMatMul3DSimpleTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 3> +BatchMatMul3DSimpleTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 3> +BatchMatMul3DSimpleTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 4> BatchMatMulNCHWSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor( + armnn::Optional<armnn::DataLayout>(armnn::DataLayout::NCHW), + armnn::Optional<armnn::DataLayout>(armnn::DataLayout::NCHW)); + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({1,1,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({1,1,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({1,1,2,2}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 2, + 3, 4 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 5, 6, + 7, 8 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 19, 22, + 43, 50 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 4>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> +BatchMatMulNCHWSimpleTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> +BatchMatMulNCHWSimpleTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 4> +BatchMatMulNCHWSimpleTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> +BatchMatMulNCHWSimpleTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> +BatchMatMulNCHWSimpleTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> +BatchMatMulNCHWSimpleTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 4> BatchMatMulNHWCSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor( + armnn::Optional<armnn::DataLayout>(armnn::DataLayout::NHWC), + armnn::Optional<armnn::DataLayout>(armnn::DataLayout::NHWC)); + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({1,2,2,1}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({1,2,2,1}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({1,2,2,1}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 2, + 3, 4 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 5, 6, + 7, 8 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 19, 22, + 43, 50 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 4>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> +BatchMatMulNHWCSimpleTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> +BatchMatMulNHWCSimpleTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 4> +BatchMatMulNHWCSimpleTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> +BatchMatMulNHWCSimpleTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> +BatchMatMulNHWCSimpleTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> +BatchMatMulNHWCSimpleTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 3> BatchMatMul3DBatchTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor(); // Arbitrary layout with no transpose/adjointing + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({2,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({2,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({2,2,2}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 2, + 3, 4, + + 9, 10, + 11, 12 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 5, 6, + 7, 8, + + 13, 14, + 15, 16 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 19, 22, + 43, 50, + + 267, 286, + 323, 346 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 3>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 3> +BatchMatMul3DBatchTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 3> +BatchMatMul3DBatchTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 3> +BatchMatMul3DBatchTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 3> +BatchMatMul3DBatchTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 3> +BatchMatMul3DBatchTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 3> +BatchMatMul3DBatchTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 3> BatchMatMul3DBroadcastTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor(); // Arbitrary layout with no transpose/adjointing + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({2,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({1,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({2,2,2}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 2, + 3, 4, + + 9, 10, + 11, 12 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 13, 14, + 15, 16 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 43, 46, + 99, 106, + + 267, 286, + 323, 346 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 3>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 3> +BatchMatMul3DBroadcastTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 3> +BatchMatMul3DBroadcastTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 3> +BatchMatMul3DBroadcastTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 3> +BatchMatMul3DBroadcastTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 3> +BatchMatMul3DBroadcastTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 3> +BatchMatMul3DBroadcastTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 3> BatchMatMul3D2DBroadcastTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor(); // Arbitrary layout with no transpose/adjointing + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({2,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({2,2,2}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 2, + 3, 4, + + 9, 10, + 11, 12 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 13, 14, + 15, 16 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 43, 46, + 99, 106, + + 267, 286, + 323, 346 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 3>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 3> +BatchMatMul3D2DBroadcastTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 3> +BatchMatMul3D2DBroadcastTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 3> +BatchMatMul3D2DBroadcastTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 3> +BatchMatMul3D2DBroadcastTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 3> +BatchMatMul3D2DBroadcastTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 3> +BatchMatMul3D2DBroadcastTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 5> BatchMatMulNDHWCNHWCTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor( + armnn::Optional<armnn::DataLayout>(armnn::DataLayout::NDHWC), + armnn::Optional<armnn::DataLayout>(armnn::DataLayout::NHWC)); + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({1,1,2,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({1,2,2,2}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({1,1,2,2,2}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 1, 20, + 3, 22, + + 2, 21, + 4, 23 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 5, 24, + 7, 26, + + 6, 25, + 8, 27 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 23, 1030, + 31, 1114, + + 34, 1079, + 46, 1167 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 5>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 5> +BatchMatMulNDHWCNHWCTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 5> +BatchMatMulNDHWCNHWCTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 5> +BatchMatMulNDHWCNHWCTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 5> +BatchMatMulNDHWCNHWCTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 5> +BatchMatMulNDHWCNHWCTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 5> +BatchMatMulNDHWCNHWCTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 2> BatchMatMul2DTinyTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor(); // Arbitrary layout with no transpose/adjointing + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({1,1}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({1,1}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({1,1}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 3 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 5 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 15 + }, qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 2>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 2> +BatchMatMul2DTinyTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 2> +BatchMatMul2DTinyTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 2> +BatchMatMul2DTinyTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 2> +BatchMatMul2DTinyTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 2> +BatchMatMul2DTinyTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 2> +BatchMatMul2DTinyTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 3> BatchMatMul3DNonSquareTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + auto descriptor = armnn::BatchMatMulDescriptor(); // Arbitrary layout with no transpose/adjointing + + float qScale = 0.0f; + int32_t qOffset = 0; + + switch(ArmnnType) + { + case armnn::DataType::QAsymmS8: + case armnn::DataType::QAsymmU8: + case armnn::DataType::QSymmS16: + qScale = 1.0f; + break; + default: + break; + } + + armnn::TensorInfo inputXInfo({2,5,3}, ArmnnType, qScale, qOffset); + armnn::TensorInfo inputYInfo({2,3,4}, ArmnnType, qScale, qOffset); + armnn::TensorInfo outputInfo({2,5,4}, ArmnnType, qScale, qOffset); + + std::vector<T> inputX = armnnUtils::QuantizedVector<T>({ + 8, 8, 4, + 6, 1, 3, + 8, 8, 3, + 8, 9, 8, + 5, 4, 4, + + 1, 8, 5, + 7, 1, 1, + 8, 7, 9, + 3, 2, 7, + 8, 5, 3 + }, qScale, qOffset); + + std::vector<T> inputY = armnnUtils::QuantizedVector<T>({ + 6, 2, 3, 2, + 6, 2, 2, 8, + 3, 7, 8, 1, + + 7, 2, 9, 5, + 2, 3, 1, 3, + 2, 7, 7, 5 + }, qScale, qOffset); + + std::vector<T> outputExpected = armnnUtils::QuantizedVector<T>({ + 108, 60, 72, 84, + 51, 35, 44, 23, + 105, 53, 64, 83, + 126, 90, 106, 96, + 66, 46, 55, 46, + + 33, 61, 52, 54, + 53, 24, 71, 43, + 88, 100, 142, 106, + 39, 61, 78, 56, + 72, 52, 98, 70 + },qScale, qOffset); + + return BatchMatMulTestImpl<ArmnnType, T, 3>(workloadFactory, + memoryManager, + tensorHandleFactory, + descriptor, + inputX, + inputY, + outputExpected, + inputXInfo, + inputYInfo, + outputInfo); +} + +template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 3> +BatchMatMul3DNonSquareTest<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 3> +BatchMatMul3DNonSquareTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float16>, 3> +BatchMatMul3DNonSquareTest<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 3> +BatchMatMul3DNonSquareTest<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 3> +BatchMatMul3DNonSquareTest<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 3> +BatchMatMul3DNonSquareTest<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory);
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