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author | Aron Virginas-Tar <Aron.Virginas-Tar@arm.com> | 2019-10-16 17:45:38 +0100 |
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committer | Áron Virginás-Tar <aron.virginas-tar@arm.com> | 2019-10-21 08:52:04 +0000 |
commit | 77bfb5e32faadb1383d48364a6f54adbff84ad80 (patch) | |
tree | 0bf5dfb48cb8d5c248baf716f02b9f481400316e /src/backends/backendsCommon/test | |
parent | 5884708e650a80e355398532bc320bbabdbb53f4 (diff) | |
download | armnn-77bfb5e32faadb1383d48364a6f54adbff84ad80.tar.gz |
IVGCVSW-3993 Add frontend and reference workload for ComparisonLayer
* Added frontend for ComparisonLayer
* Added RefComparisonWorkload
* Deprecated and removed Equal and Greater layers and workloads
* Updated tests to ensure backward compatibility
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Id50c880be1b567c531efff919c0c366d0a71cbe9
Diffstat (limited to 'src/backends/backendsCommon/test')
7 files changed, 274 insertions, 201 deletions
diff --git a/src/backends/backendsCommon/test/ArithmeticTestImpl.hpp b/src/backends/backendsCommon/test/ArithmeticTestImpl.hpp deleted file mode 100644 index d0e85dd31d..0000000000 --- a/src/backends/backendsCommon/test/ArithmeticTestImpl.hpp +++ /dev/null @@ -1,113 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// -#pragma once - -#include "CommonTestUtils.hpp" - -#include <ResolveType.hpp> - -#include <armnn/INetwork.hpp> - -#include <boost/test/unit_test.hpp> - -#include <vector> - -namespace -{ - -template<armnn::DataType ArmnnTypeInput, armnn::DataType ArmnnTypeOutput> -INetworkPtr CreateArithmeticNetwork(const std::vector<TensorShape>& inputShapes, - const TensorShape& outputShape, - const LayerType type, - const float qScale = 1.0f, - const int32_t qOffset = 0) -{ - using namespace armnn; - - // Builds up the structure of the network. - INetworkPtr net(INetwork::Create()); - - IConnectableLayer* arithmeticLayer = nullptr; - - switch(type){ - case LayerType::Equal: arithmeticLayer = net->AddEqualLayer("equal"); break; - case LayerType::Greater: arithmeticLayer = net->AddGreaterLayer("greater"); break; - default: BOOST_TEST_FAIL("Non-Arithmetic layer type called."); - } - - for (unsigned int i = 0; i < inputShapes.size(); ++i) - { - TensorInfo inputTensorInfo(inputShapes[i], ArmnnTypeInput, qScale, qOffset); - IConnectableLayer* input = net->AddInputLayer(boost::numeric_cast<LayerBindingId>(i)); - Connect(input, arithmeticLayer, inputTensorInfo, 0, i); - } - - TensorInfo outputTensorInfo(outputShape, ArmnnTypeOutput, qScale, qOffset); - IConnectableLayer* output = net->AddOutputLayer(0, "output"); - Connect(arithmeticLayer, output, outputTensorInfo, 0, 0); - - return net; -} - -template<armnn::DataType ArmnnInputType, - armnn::DataType ArmnnOutputType, - typename TInput = armnn::ResolveType<ArmnnInputType>, - typename TOutput = armnn::ResolveType<ArmnnOutputType>> -void ArithmeticSimpleEndToEnd(const std::vector<BackendId>& backends, - const LayerType type, - const std::vector<TOutput> expectedOutput) -{ - using namespace armnn; - - const std::vector<TensorShape> inputShapes{{ 2, 2, 2, 2 }, { 2, 2, 2, 2 }}; - const TensorShape& outputShape = { 2, 2, 2, 2 }; - - // Builds up the structure of the network - INetworkPtr net = CreateArithmeticNetwork<ArmnnInputType, ArmnnOutputType>(inputShapes, outputShape, type); - - BOOST_TEST_CHECKPOINT("create a network"); - - const std::vector<TInput> input0({ 1, 1, 1, 1, 5, 5, 5, 5, - 3, 3, 3, 3, 4, 4, 4, 4 }); - - const std::vector<TInput> input1({ 1, 1, 1, 1, 3, 3, 3, 3, - 5, 5, 5, 5, 4, 4, 4, 4 }); - - std::map<int, std::vector<TInput>> inputTensorData = {{ 0, input0 }, { 1, input1 }}; - std::map<int, std::vector<TOutput>> expectedOutputData = {{ 0, expectedOutput }}; - - EndToEndLayerTestImpl<ArmnnInputType, ArmnnOutputType>(move(net), inputTensorData, expectedOutputData, backends); -} - -template<armnn::DataType ArmnnInputType, - armnn::DataType ArmnnOutputType, - typename TInput = armnn::ResolveType<ArmnnInputType>, - typename TOutput = armnn::ResolveType<ArmnnOutputType>> -void ArithmeticBroadcastEndToEnd(const std::vector<BackendId>& backends, - const LayerType type, - const std::vector<TOutput> expectedOutput) -{ - using namespace armnn; - - const std::vector<TensorShape> inputShapes{{ 1, 2, 2, 3 }, { 1, 1, 1, 3 }}; - const TensorShape& outputShape = { 1, 2, 2, 3 }; - - // Builds up the structure of the network - INetworkPtr net = CreateArithmeticNetwork<ArmnnInputType, ArmnnOutputType>(inputShapes, outputShape, type); - - BOOST_TEST_CHECKPOINT("create a network"); - - const std::vector<TInput> input0({ 1, 2, 3, 1, 0, 6, - 7, 8, 9, 10, 11, 12 }); - - const std::vector<TInput> input1({ 1, 1, 3 }); - - std::map<int, std::vector<TInput>> inputTensorData = {{ 0, input0 }, { 1, input1 }}; - std::map<int, std::vector<TOutput>> expectedOutputData = {{ 0, expectedOutput }}; - - EndToEndLayerTestImpl<ArmnnInputType, ArmnnOutputType>(move(net), inputTensorData, expectedOutputData, backends); -} - -} // anonymous namespace diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt index 797dc90952..7449e69dcd 100644 --- a/src/backends/backendsCommon/test/CMakeLists.txt +++ b/src/backends/backendsCommon/test/CMakeLists.txt @@ -10,6 +10,7 @@ list(APPEND armnnBackendsCommonUnitTests_sources BackendRegistryTests.cpp CommonTestUtils.cpp CommonTestUtils.hpp + ComparisonEndToEndTestImpl.hpp DataLayoutUtils.hpp DataTypeUtils.hpp DepthToSpaceEndToEndTestImpl.hpp @@ -58,6 +59,7 @@ list(APPEND armnnBackendsCommonUnitTests_sources layerTests/BatchNormalizationTestImpl.cpp layerTests/BatchNormalizationTestImpl.hpp layerTests/BatchToSpaceNdTestImpl.hpp + layerTests/ComparisonTestImpl.hpp layerTests/ConcatTestImpl.cpp layerTests/ConcatTestImpl.hpp layerTests/ConstantTestImpl.cpp diff --git a/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp new file mode 100644 index 0000000000..dc53b7b246 --- /dev/null +++ b/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp @@ -0,0 +1,103 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// +#pragma once + +#include "CommonTestUtils.hpp" + +#include <ResolveType.hpp> + +#include <armnn/INetwork.hpp> + +#include <boost/test/unit_test.hpp> + +#include <vector> + +namespace +{ + +template<armnn::DataType ArmnnTypeInput> +INetworkPtr CreateComparisonNetwork(const std::vector<TensorShape>& inputShapes, + const TensorShape& outputShape, + ComparisonOperation operation, + const float qScale = 1.0f, + const int32_t qOffset = 0) +{ + using namespace armnn; + + INetworkPtr net(INetwork::Create()); + + ComparisonDescriptor descriptor(operation); + IConnectableLayer* comparisonLayer = net->AddComparisonLayer(descriptor, "comparison"); + + for (unsigned int i = 0; i < inputShapes.size(); ++i) + { + TensorInfo inputTensorInfo(inputShapes[i], ArmnnTypeInput, qScale, qOffset); + IConnectableLayer* input = net->AddInputLayer(boost::numeric_cast<LayerBindingId>(i)); + Connect(input, comparisonLayer, inputTensorInfo, 0, i); + } + + TensorInfo outputTensorInfo(outputShape, DataType::Boolean, qScale, qOffset); + IConnectableLayer* output = net->AddOutputLayer(0, "output"); + Connect(comparisonLayer, output, outputTensorInfo, 0, 0); + + return net; +} + +template<armnn::DataType ArmnnInType, + typename TInput = armnn::ResolveType<ArmnnInType>> +void ComparisonSimpleEndToEnd(const std::vector<BackendId>& backends, + ComparisonOperation operation, + const std::vector<uint8_t> expectedOutput) +{ + using namespace armnn; + + const std::vector<TensorShape> inputShapes{{ 2, 2, 2, 2 }, { 2, 2, 2, 2 }}; + const TensorShape& outputShape = { 2, 2, 2, 2 }; + + // Builds up the structure of the network + INetworkPtr net = CreateComparisonNetwork<ArmnnInType>(inputShapes, outputShape, operation); + + BOOST_TEST_CHECKPOINT("create a network"); + + const std::vector<TInput> input0({ 1, 1, 1, 1, 5, 5, 5, 5, + 3, 3, 3, 3, 4, 4, 4, 4 }); + + const std::vector<TInput> input1({ 1, 1, 1, 1, 3, 3, 3, 3, + 5, 5, 5, 5, 4, 4, 4, 4 }); + + std::map<int, std::vector<TInput>> inputTensorData = {{ 0, input0 }, { 1, input1 }}; + std::map<int, std::vector<uint8_t>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<ArmnnInType, DataType::Boolean>(move(net), inputTensorData, expectedOutputData, backends); +} + +template<armnn::DataType ArmnnInType, + typename TInput = armnn::ResolveType<ArmnnInType>> +void ComparisonBroadcastEndToEnd(const std::vector<BackendId>& backends, + ComparisonOperation operation, + const std::vector<uint8_t> expectedOutput) +{ + using namespace armnn; + + const std::vector<TensorShape> inputShapes{{ 1, 2, 2, 3 }, { 1, 1, 1, 3 }}; + const TensorShape& outputShape = { 1, 2, 2, 3 }; + + // Builds up the structure of the network + INetworkPtr net = CreateComparisonNetwork<ArmnnInType>(inputShapes, outputShape, operation); + + BOOST_TEST_CHECKPOINT("create a network"); + + const std::vector<TInput> input0({ 1, 2, 3, 1, 0, 6, + 7, 8, 9, 10, 11, 12 }); + + const std::vector<TInput> input1({ 1, 1, 3 }); + + std::map<int, std::vector<TInput>> inputTensorData = {{ 0, input0 }, { 1, input1 }}; + std::map<int, std::vector<uint8_t>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<ArmnnInType, DataType::Boolean>(move(net), inputTensorData, expectedOutputData, backends); +} + +} // anonymous namespace diff --git a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp index 907285c5cf..9bddae9759 100644 --- a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp +++ b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp @@ -397,6 +397,8 @@ DECLARE_LAYER_POLICY_2_PARAM(BatchNormalization) DECLARE_LAYER_POLICY_2_PARAM(BatchToSpaceNd) +DECLARE_LAYER_POLICY_2_PARAM(Comparison) + DECLARE_LAYER_POLICY_2_PARAM(Concat) DECLARE_LAYER_POLICY_1_PARAM(Constant) @@ -421,8 +423,6 @@ DECLARE_LAYER_POLICY_1_PARAM(Dequantize) DECLARE_LAYER_POLICY_2_PARAM(DetectionPostProcess) -DECLARE_LAYER_POLICY_1_PARAM(Equal) - DECLARE_LAYER_POLICY_2_PARAM(FakeQuantization) DECLARE_LAYER_POLICY_1_PARAM(Floor) @@ -431,8 +431,6 @@ DECLARE_LAYER_POLICY_2_PARAM(FullyConnected) DECLARE_LAYER_POLICY_1_PARAM(Gather) -DECLARE_LAYER_POLICY_1_PARAM(Greater) - DECLARE_LAYER_POLICY_CUSTOM_PARAM(Input, armnn::LayerBindingId) DECLARE_LAYER_POLICY_2_PARAM(InstanceNormalization) diff --git a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.hpp new file mode 100644 index 0000000000..6ce9b306c0 --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.hpp @@ -0,0 +1,126 @@ +// +// Copyright © 2019 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "LayerTestResult.hpp" + +#include <armnn/ArmNN.hpp> + +#include <ResolveType.hpp> + +#include <backendsCommon/IBackendInternal.hpp> +#include <backendsCommon/Workload.hpp> +#include <backendsCommon/WorkloadData.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +#include <backendsCommon/test/TensorCopyUtils.hpp> +#include <backendsCommon/test/WorkloadTestUtils.hpp> + +#include <test/TensorHelpers.hpp> + +template <std::size_t NumDims, + armnn::DataType ArmnnInType, + typename InType = armnn::ResolveType<ArmnnInType>> +LayerTestResult<uint8_t, NumDims> ComparisonTestImpl( + armnn::IWorkloadFactory & workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager, + const armnn::ComparisonDescriptor& descriptor, + const unsigned int shape0[NumDims], + std::vector<InType> values0, + float quantScale0, + int quantOffset0, + const unsigned int shape1[NumDims], + std::vector<InType> values1, + float quantScale1, + int quantOffset1, + const unsigned int outShape[NumDims], + std::vector<uint8_t> outValues, + float outQuantScale, + int outQuantOffset) +{ + armnn::TensorInfo inputTensorInfo0{NumDims, shape0, ArmnnInType}; + armnn::TensorInfo inputTensorInfo1{NumDims, shape1, ArmnnInType}; + armnn::TensorInfo outputTensorInfo{NumDims, outShape, armnn::DataType::Boolean}; + + auto input0 = MakeTensor<InType, NumDims>(inputTensorInfo0, values0); + auto input1 = MakeTensor<InType, NumDims>(inputTensorInfo1, values1); + + inputTensorInfo0.SetQuantizationScale(quantScale0); + inputTensorInfo0.SetQuantizationOffset(quantOffset0); + + inputTensorInfo1.SetQuantizationScale(quantScale1); + inputTensorInfo1.SetQuantizationOffset(quantOffset1); + + outputTensorInfo.SetQuantizationScale(outQuantScale); + outputTensorInfo.SetQuantizationOffset(outQuantOffset); + + LayerTestResult<uint8_t, NumDims> ret(outputTensorInfo); + + std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); + std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); + std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::ComparisonQueueDescriptor qDescriptor; + qDescriptor.m_Parameters = descriptor; + + armnn::WorkloadInfo info; + AddInputToWorkload(qDescriptor, info, inputTensorInfo0, inputHandle0.get()); + AddInputToWorkload(qDescriptor, info, inputTensorInfo1, inputHandle1.get()); + AddOutputToWorkload(qDescriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateComparison(qDescriptor, info); + + inputHandle0->Allocate(); + inputHandle1->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle0.get(), input0.origin()); + CopyDataToITensorHandle(inputHandle1.get(), input1.origin()); + + workload->PostAllocationConfigure(); + ExecuteWorkload(*workload, memoryManager); + + CopyDataFromITensorHandle(ret.output.origin(), outputHandle.get()); + + ret.outputExpected = MakeTensor<uint8_t, NumDims>(outputTensorInfo, outValues); + ret.compareBoolean = true; + + return ret; +} + +template <std::size_t NumDims, + armnn::DataType ArmnnInType, + typename InType = armnn::ResolveType<ArmnnInType>> +LayerTestResult<uint8_t, NumDims> ComparisonTestImpl( + armnn::IWorkloadFactory & workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager, + const armnn::ComparisonDescriptor& descriptor, + const unsigned int shape0[NumDims], + std::vector<InType> values0, + const unsigned int shape1[NumDims], + std::vector<InType> values1, + const unsigned int outShape[NumDims], + std::vector<uint8_t> outValues, + float qScale = 10.f, + int qOffset = 0) +{ + return ComparisonTestImpl<NumDims, ArmnnInType>( + workloadFactory, + memoryManager, + descriptor, + shape0, + values0, + qScale, + qOffset, + shape1, + values1, + qScale, + qOffset, + outShape, + outValues, + qScale, + qOffset); +} diff --git a/src/backends/backendsCommon/test/layerTests/EqualTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/EqualTestImpl.cpp index b0b613c137..a3d2b2796f 100644 --- a/src/backends/backendsCommon/test/layerTests/EqualTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/EqualTestImpl.cpp @@ -4,18 +4,10 @@ // #include "EqualTestImpl.hpp" -#include "ElementwiseTestImpl.hpp" -#include <Half.hpp> +#include "ComparisonTestImpl.hpp" -template<> -std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::EqualQueueDescriptor>( - const armnn::IWorkloadFactory& workloadFactory, - const armnn::WorkloadInfo& info, - const armnn::EqualQueueDescriptor& descriptor) -{ - return workloadFactory.CreateEqual(descriptor, info); -} +#include <Half.hpp> LayerTestResult<uint8_t, 4> EqualSimpleTest(armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) @@ -39,9 +31,10 @@ LayerTestResult<uint8_t, 4> EqualSimpleTest(armnn::IWorkloadFactory& workloadFac std::vector<uint8_t> output({ 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1 }); - return ElementwiseTestHelper<4, armnn::EqualQueueDescriptor, armnn::DataType::Float32, armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float32>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape, input0, shape, @@ -62,9 +55,10 @@ LayerTestResult<uint8_t, 4> EqualBroadcast1ElementTest( std::vector<uint8_t> output({ 1, 0, 0, 0, 0, 0, 0, 0}); - return ElementwiseTestHelper<4, armnn::EqualQueueDescriptor, armnn::DataType::Float32, armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float32>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape0, input0, shape1, @@ -88,9 +82,10 @@ LayerTestResult<uint8_t, 4> EqualBroadcast1DVectorTest( std::vector<uint8_t> output({ 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 }); - return ElementwiseTestHelper<4, armnn::EqualQueueDescriptor, armnn::DataType::Float32, armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float32>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape0, input0, shape1, @@ -117,12 +112,10 @@ LayerTestResult<uint8_t, 4> EqualFloat16Test( std::vector<uint8_t> output({ 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0 }); - return ElementwiseTestHelper<4, - armnn::EqualQueueDescriptor, - armnn::DataType::Float16, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float16>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape, input0, shape, @@ -148,12 +141,10 @@ LayerTestResult<uint8_t, 4> EqualBroadcast1ElementFloat16Test( std::vector<uint8_t> output({ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }); - return ElementwiseTestHelper<4, - armnn::EqualQueueDescriptor, - armnn::DataType::Float16, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float16>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape0, input0, shape1, @@ -179,12 +170,10 @@ LayerTestResult<uint8_t, 4> EqualBroadcast1DVectorFloat16Test( std::vector<uint8_t> output({ 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 }); - return ElementwiseTestHelper<4, - armnn::EqualQueueDescriptor, - armnn::DataType::Float16, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float16>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape0, input0, shape1, @@ -209,12 +198,10 @@ LayerTestResult<uint8_t, 4> EqualUint8Test( std::vector<uint8_t> output({ 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0 }); - return ElementwiseTestHelper<4, - armnn::EqualQueueDescriptor, - armnn::DataType::QuantisedAsymm8, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::QuantisedAsymm8>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape, input0, shape, @@ -238,12 +225,10 @@ LayerTestResult<uint8_t, 4> EqualBroadcast1ElementUint8Test( std::vector<uint8_t> output({ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }); - return ElementwiseTestHelper<4, - armnn::EqualQueueDescriptor, - armnn::DataType::QuantisedAsymm8, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::QuantisedAsymm8>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape0, input0, shape1, @@ -267,12 +252,10 @@ LayerTestResult<uint8_t, 4> EqualBroadcast1DVectorUint8Test( std::vector<uint8_t> output({ 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 }); - return ElementwiseTestHelper<4, - armnn::EqualQueueDescriptor, - armnn::DataType::QuantisedAsymm8, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::QuantisedAsymm8>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Equal), shape0, input0, shape1, diff --git a/src/backends/backendsCommon/test/layerTests/GreaterTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/GreaterTestImpl.cpp index 0148216285..271bc235a9 100644 --- a/src/backends/backendsCommon/test/layerTests/GreaterTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/GreaterTestImpl.cpp @@ -4,18 +4,10 @@ // #include "GreaterTestImpl.hpp" -#include "ElementwiseTestImpl.hpp" -#include <Half.hpp> +#include "ComparisonTestImpl.hpp" -template<> -std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::GreaterQueueDescriptor>( - const armnn::IWorkloadFactory& workloadFactory, - const armnn::WorkloadInfo& info, - const armnn::GreaterQueueDescriptor& descriptor) -{ - return workloadFactory.CreateGreater(descriptor, info); -} +#include <Half.hpp> LayerTestResult<uint8_t, 4> GreaterSimpleTest(armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) @@ -45,12 +37,10 @@ LayerTestResult<uint8_t, 4> GreaterSimpleTest(armnn::IWorkloadFactory& workloadF 0, 0, 0, 0, 0, 0, 0, 0 }; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::Float32, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float32>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape, input0, shape, @@ -71,12 +61,10 @@ LayerTestResult<uint8_t, 4> GreaterBroadcast1ElementTest( std::vector<uint8_t> output = { 0, 1, 1, 1, 1, 1, 1, 1}; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::Float32, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float32>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape0, input0, shape1, @@ -106,12 +94,10 @@ LayerTestResult<uint8_t, 4> GreaterBroadcast1DVectorTest( 1, 1, 1, 1, 1, 1 }; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::Float32, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float32>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape0, input0, shape1, @@ -151,12 +137,10 @@ LayerTestResult<uint8_t, 4> GreaterFloat16Test( 0, 0, 0, 0, 0, 0, 0, 0 }; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::Float16, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4,armnn::DataType::Float16>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape, input0, shape, @@ -179,12 +163,10 @@ LayerTestResult<uint8_t, 4> GreaterBroadcast1ElementFloat16Test( std::vector<uint8_t> output = { 0, 1, 1, 1, 1, 1, 1, 1}; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::Float16, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float16>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape0, input0, shape1, @@ -198,7 +180,7 @@ LayerTestResult<uint8_t, 4> GreaterBroadcast1DVectorFloat16Test( const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { using namespace half_float::literal; - + const unsigned int shape0[] = { 1, 2, 2, 3 }; const unsigned int shape1[] = { 1, 1, 1, 3 }; @@ -216,12 +198,10 @@ LayerTestResult<uint8_t, 4> GreaterBroadcast1DVectorFloat16Test( 1, 1, 1, 1, 1, 1 }; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::Float16, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::Float16>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape0, input0, shape1, @@ -255,12 +235,10 @@ LayerTestResult<uint8_t, 4> GreaterUint8Test( 1, 1, 1, 1, 0, 0, 0, 0 }; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::QuantisedAsymm8, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::QuantisedAsymm8>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape, input0, shape, @@ -290,12 +268,10 @@ LayerTestResult<uint8_t, 4> GreaterBroadcast1ElementUint8Test( 1, 1, 1, 1, 1, 1 }; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::QuantisedAsymm8, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::QuantisedAsymm8>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape0, input0, shape1, @@ -325,12 +301,10 @@ LayerTestResult<uint8_t, 4> GreaterBroadcast1DVectorUint8Test( 1, 1, 1, 1, 1, 1 }; - return ElementwiseTestHelper<4, - armnn::GreaterQueueDescriptor, - armnn::DataType::QuantisedAsymm8, - armnn::DataType::Boolean>( + return ComparisonTestImpl<4, armnn::DataType::QuantisedAsymm8>( workloadFactory, memoryManager, + armnn::ComparisonDescriptor(armnn::ComparisonOperation::Greater), shape0, input0, shape1, |