| // |
| // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "AvgPool2DIgnoreValueChecker.hpp" |
| #include "QuantizeChecker.hpp" |
| #include "SplitChecker.hpp" |
| |
| #include <armnn/IRuntime.hpp> |
| |
| using namespace armnn; |
| using namespace tosa; |
| |
| TEST_SUITE("TosaOperatorMappingOneToManyTests") |
| { |
| TEST_CASE("GetTosaMapping_AvgPool2DIgnoreValueLayer") |
| { |
| armnn::Pooling2dDescriptor descriptor; |
| descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| descriptor.m_PadLeft = 1; |
| descriptor.m_PadRight = 1; |
| descriptor.m_PadTop = 1; |
| descriptor.m_PadBottom = 1; |
| descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| |
| armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); |
| armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); |
| |
| std::vector<std::vector<int32_t>> inputShape = {{ 1, 1, 4, 4 }}; |
| std::vector<std::vector<int32_t>> intermediateShape = {{ 1, 1, 6, 6 }}; |
| std::vector<std::vector<int32_t>> outputShape = {{ 1, 1, 3, 3 }}; |
| |
| TosaSerializationBasicBlock* basicBlock = |
| GetTosaMapping(nullptr, LayerType::Pooling2d, {&inputTensorInfo}, {&outputTensorInfo}, descriptor); |
| VerifyAvgPool2DIgnoreValue(basicBlock, |
| inputShape, |
| outputShape, |
| intermediateShape, |
| descriptor); |
| } |
| |
| TEST_CASE("GetTosaMappingFromLayer_AvgPool2DIgnoreValueLayer") |
| { |
| IRuntime::CreationOptions options; |
| IRuntimePtr runtime(IRuntime::Create(options)); |
| |
| // Builds up the structure of the network. |
| INetworkPtr net(INetwork::Create()); |
| |
| armnn::Pooling2dDescriptor descriptor; |
| descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| descriptor.m_PadLeft = 1; |
| descriptor.m_PadRight = 1; |
| descriptor.m_PadTop = 1; |
| descriptor.m_PadBottom = 1; |
| descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| |
| IConnectableLayer* input0 = net->AddInputLayer(0, "input0"); |
| IConnectableLayer* pool = net->AddPooling2dLayer(descriptor, "pool"); |
| IConnectableLayer* output = net->AddOutputLayer(0, "output"); |
| |
| input0->GetOutputSlot(0).Connect(pool->GetInputSlot(0)); |
| pool->GetOutputSlot(0).Connect(output->GetInputSlot(0)); |
| |
| armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); |
| armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); |
| |
| std::vector<std::vector<int32_t>> inputShape = {{ 1, 1, 4, 4 }}; |
| std::vector<std::vector<int32_t>> intermediateShape = {{ 1, 1, 6, 6 }}; |
| std::vector<std::vector<int32_t>> outputShape = {{ 1, 1, 3, 3 }}; |
| |
| input0->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| pool->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| |
| TosaSerializationBasicBlock* basicBlock = |
| GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(pool)); |
| VerifyAvgPool2DIgnoreValue(basicBlock, |
| inputShape, |
| outputShape, |
| intermediateShape, |
| descriptor); |
| } |
| |
| TEST_CASE("GetTosaMapping_QuantizeLayer") |
| { |
| NullDescriptor descriptor; |
| DataType outputDataType = DataType::Signed32; |
| |
| TensorInfo inputTensorInfo({ 1, 3, 3, 1 }, DataType::Float32); |
| TensorInfo outputTensorInfo({ 1, 3, 3, 1 }, outputDataType); |
| std::vector<int32_t> shape = { 1, 3, 3, 1 }; |
| |
| TosaSerializationBasicBlock* basicBlock = |
| GetTosaMapping(nullptr, LayerType::Quantize, {&inputTensorInfo}, {&outputTensorInfo}, descriptor); |
| VerifyQuantize(basicBlock, shape, ArmNNToDType(DataType::Float32), ArmNNToDType(outputDataType)); |
| } |
| TEST_CASE("GetTosaMappingFromLayer_QuantizeLayer") |
| { |
| IRuntime::CreationOptions options; |
| IRuntimePtr runtime(IRuntime::Create(options)); |
| // Builds up the structure of the network. |
| INetworkPtr net(INetwork::Create()); |
| NullDescriptor descriptor; |
| DataType outputDataType = DataType::Signed32; |
| |
| IConnectableLayer* input0 = net->AddInputLayer(0, "input0"); |
| IConnectableLayer* quantize = net->AddQuantizeLayer("quantize"); |
| IConnectableLayer* output = net->AddOutputLayer(0, "output"); |
| |
| input0->GetOutputSlot(0).Connect(quantize->GetInputSlot(0)); |
| quantize->GetOutputSlot(0).Connect(output->GetInputSlot(0)); |
| |
| armnn::TensorInfo inputTensorInfo({ 1, 3, 3, 1 }, DataType::Float32); |
| armnn::TensorInfo outputTensorInfo({ 1, 3, 3, 1 }, outputDataType); |
| std::vector<int32_t> shape = { 1, 3, 3, 1 }; |
| |
| input0->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| quantize->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| |
| TosaSerializationBasicBlock* basicBlock = GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(quantize)); |
| VerifyQuantize(basicBlock, shape, ArmNNToDType(DataType::Float32), ArmNNToDType(outputDataType)); |
| } |
| |
| TEST_CASE("GetTosaMapping_SplitLayer") |
| { |
| const unsigned int numViews = 3; |
| const unsigned int numDimensions = 4; |
| armnn::ViewsDescriptor descriptor(numViews, numDimensions); |
| descriptor.SetAxis(static_cast<int32_t>(1)); |
| |
| std::vector<std::vector<int32_t>> inShape = {{ 1, 18, 4, 4 }}; |
| std::vector<std::vector<int32_t>> outShape = {{ 1, 6, 4, 4 },{ 1, 6, 4, 4 },{ 1, 6, 4, 4 }}; |
| |
| armnn::TensorInfo inputTensorInfo({1, 18, 4, 4}, DataType::Float32); |
| armnn::TensorInfo outputTensorInfo({1, 6, 4, 4}, DataType::Float32); |
| |
| TosaSerializationBasicBlock* basicBlock = |
| GetTosaMapping(nullptr, LayerType::Splitter, {&inputTensorInfo}, {&outputTensorInfo}, descriptor); |
| |
| VerifySplit(basicBlock, |
| inShape, |
| outShape, |
| descriptor); |
| } |
| |
| TEST_CASE("GetTosaMappingFromLayer_SplitLayer") |
| { |
| IRuntime::CreationOptions options; |
| IRuntimePtr runtime(IRuntime::Create(options)); |
| |
| // Builds up the structure of the network. |
| INetworkPtr net(INetwork::Create()); |
| |
| const unsigned int numViews = 3; |
| const unsigned int numDimensions = 4; |
| armnn::ViewsDescriptor descriptor(numViews, numDimensions); |
| descriptor.SetAxis(static_cast<int32_t>(1)); |
| |
| std::vector<std::vector<int32_t>> inShape = {{ 1, 18, 4, 4 }}; |
| std::vector<std::vector<int32_t>> outShape = {{ 1, 6, 4, 4 },{ 1, 6, 4, 4 },{ 1, 6, 4, 4 }}; |
| |
| IConnectableLayer* input0 = net->AddInputLayer(0, "input0"); |
| IConnectableLayer* split = net->AddSplitterLayer(descriptor, "split"); |
| IConnectableLayer* output0 = net->AddOutputLayer(0, "output0"); |
| IConnectableLayer* output1 = net->AddOutputLayer(1, "output1"); |
| IConnectableLayer* output2 = net->AddOutputLayer(2, "output2"); |
| |
| input0->GetOutputSlot(0).Connect(split->GetInputSlot(0)); |
| split->GetOutputSlot(0).Connect(output0->GetInputSlot(0)); |
| split->GetOutputSlot(1).Connect(output1->GetInputSlot(0)); |
| split->GetOutputSlot(2).Connect(output2->GetInputSlot(0)); |
| |
| armnn::TensorInfo inputTensorInfo({1, 18, 4, 4}, DataType::Float32); |
| armnn::TensorInfo outputTensorInfo({1, 6, 4, 4}, DataType::Float32); |
| |
| input0->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| split->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| split->GetOutputSlot(1).SetTensorInfo(outputTensorInfo); |
| split->GetOutputSlot(2).SetTensorInfo(outputTensorInfo); |
| |
| TosaSerializationBasicBlock* basicBlock = GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(split)); |
| |
| VerifySplit(basicBlock, |
| inShape, |
| outShape, |
| descriptor); |
| } |
| } |