From b30e6554ad41f21c8326e387aa2c1f8a5d4e6445 Mon Sep 17 00:00:00 2001 From: Cathal Corbett Date: Wed, 7 Dec 2022 11:50:50 +0000 Subject: IVGCVSW-7174 Add Reshape support to TOSA Reference Backend * Spelling corrections and code refactors added to TosaCommon * TosaDTypeToString() implemented and used in TosaRef IsLayerSupported() instead of enum integer. * Using namespace armnn in TosaCommon OneToOneMappingTests and TosaReference TosaRefLayerSupportTests instead of armnn::ClassName. * Updated VerifyTosaAttribute() to also verify certain attributes from input and output shapes. Signed-off-by: Cathal Corbett Change-Id: I71dfca404d081a665f748ab724153c6dc36b7eca --- src/backends/tosaCommon/TosaMappings.cpp | 5 + .../operatorMappings/AdditionOperator.cpp | 2 +- .../AvgPool2DIgnoreValueOperator.cpp | 2 +- .../tosaCommon/operatorMappings/CMakeLists.txt | 2 + .../operatorMappings/Pooling2DOperator.cpp | 2 +- .../operatorMappings/ReshapeOperator.cpp | 54 ++++++++ .../operatorMappings/ReshapeOperator.hpp | 20 +++ .../operatorMappings/TosaCommonOperators.hpp | 3 +- .../operatorMappings/TosaOperatorUtils.hpp | 57 +++++--- .../test/AvgPool2DIgnoreValueChecker.hpp | 18 ++- .../tosaCommon/test/OneToOneMappingTests.cpp | 146 +++++++++++++++------ src/backends/tosaCommon/test/TosaTestUtils.hpp | 52 +++++++- 12 files changed, 285 insertions(+), 78 deletions(-) create mode 100644 src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp create mode 100644 src/backends/tosaCommon/operatorMappings/ReshapeOperator.hpp (limited to 'src/backends/tosaCommon') diff --git a/src/backends/tosaCommon/TosaMappings.cpp b/src/backends/tosaCommon/TosaMappings.cpp index 00ba429555..318735db77 100644 --- a/src/backends/tosaCommon/TosaMappings.cpp +++ b/src/backends/tosaCommon/TosaMappings.cpp @@ -57,6 +57,11 @@ TosaSerializationBasicBlock* GetTosaMapping(const Layer* layer, return ConvertPooling2DToTosaOperator(layer, inputs, outputs, poolDesc); } } + case LayerType::Reshape: + { + auto reshapeDesc = PolymorphicDowncast(&descriptor); + return ConvertReshapeToTosaOperator(layer, inputs, outputs, reshapeDesc); + } default: { return CreateEmptyTosaSerializationBasicBlock(); diff --git a/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp b/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp index 66ca869ac4..f1fb34c5e2 100644 --- a/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp +++ b/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp @@ -50,7 +50,7 @@ TosaSerializationBasicBlock* ConvertAdditionToTosaOperator(const Layer* layer, auto* outputTensor0 = new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}); // operatorInputNames/operatorOutputNames ends up being the same as - // blockInputNames/blockOutputNames for one-to-one ArmNN to Tosa mappings + // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings return new TosaSerializationBasicBlock(blockName, // name {op}, // operators {inputTensor0, inputTensor1, outputTensor0}, // tensors diff --git a/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp b/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp index 2601a6243d..7e7631dcef 100644 --- a/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp +++ b/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp @@ -101,7 +101,7 @@ TosaSerializationBasicBlock* ConvertAvgPool2DIgnoreValueToTosaOperator(const Lay auto* outputTensor = new TosaSerializationTensor(poolOutputName, outputShape, outputDType, {}); // operatorInputNames/operatorOutputNames ends up being the same as - // blockInputNames/blockOutputNames for one-to-one ArmNN to Tosa mappings + // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings return new TosaSerializationBasicBlock(blockName, // name {opPad, opPool}, // operators {inputTensor, intermediateTensor, outputTensor}, // tensors diff --git a/src/backends/tosaCommon/operatorMappings/CMakeLists.txt b/src/backends/tosaCommon/operatorMappings/CMakeLists.txt index b256eddda1..7733d01abb 100644 --- a/src/backends/tosaCommon/operatorMappings/CMakeLists.txt +++ b/src/backends/tosaCommon/operatorMappings/CMakeLists.txt @@ -14,6 +14,8 @@ list(APPEND armnnTosaBackendOperators_sources Conv2dOperator.cpp Pooling2DOperator.hpp Pooling2DOperator.cpp + ReshapeOperator.hpp + ReshapeOperator.cpp TosaOperatorUtils.hpp ) diff --git a/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp b/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp index eaeb8a4cde..265901e1ae 100644 --- a/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp +++ b/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp @@ -56,7 +56,7 @@ TosaSerializationBasicBlock* ConvertPooling2DToTosaOperator(const Layer* layer, auto* outputTensor0 = new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}); // operatorInputNames/operatorOutputNames ends up being the same as - // blockInputNames/blockOutputNames for one-to-one ArmNN to Tosa mappings + // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings return new TosaSerializationBasicBlock(blockName, // name {op}, // operators {inputTensor0, outputTensor0}, // tensors diff --git a/src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp b/src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp new file mode 100644 index 0000000000..b88a6ef894 --- /dev/null +++ b/src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp @@ -0,0 +1,54 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ReshapeOperator.hpp" + +TosaSerializationBasicBlock* ConvertReshapeToTosaOperator(const Layer* layer, + const std::vector& inputs, + const std::vector& outputs, + const ReshapeDescriptor* reshapeDescriptor) +{ + std::string inputName = std::string("input0_"); + std::string outputName = std::string("output0_"); + std::string blockName = std::string("Op_RESHAPE_block_") + GetUniqueTosaMappingID(); + + // If a layer is present then the block will be used for execution, so input and output names need to be determined + // using the previous and following layers so the graph is connected correctly. For validation this doesn't matter. + if(layer != nullptr) + { + // Get the layers connected to the input slots and determine unique layer names. + Layer& connectedLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer(); + inputName = GenerateUniqueName(connectedLayer, 0); + + // Get the layer connected to the output slot and determine unique layer name. + Layer& connectedOutputLayer = layer->GetOutputSlot().GetConnection(0)->GetOwningLayer(); + outputName = GenerateUniqueName(connectedOutputLayer, 0); + } + + TosaReshapeAttribute attribute(GetTosaTensorShape(reshapeDescriptor->m_TargetShape)); + + auto* op = new TosaSerializationOperator(Op_RESHAPE, + Attribute_ReshapeAttribute, + &attribute, + {inputName}, + {outputName}); + + std::vector inputShape = GetTosaTensorShape(inputs[0]->GetShape()); + DType inputDType = ArmNNToDType(inputs[0]->GetDataType()); + + std::vector outputShape = GetTosaTensorShape(outputs[0]->GetShape()); + DType outputDType = ArmNNToDType(outputs[0]->GetDataType()); + + auto* inputTensor = new TosaSerializationTensor(inputName, inputShape, inputDType, {}); + auto* outputTensor = new TosaSerializationTensor(outputName, outputShape, outputDType, {}); + + // operatorInputNames/operatorOutputNames ends up being the same as + // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings + return new TosaSerializationBasicBlock(blockName, // name + {op}, // operators + {inputTensor, outputTensor}, // tensors + {inputName}, // inputs + {outputName}); // outputs +} \ No newline at end of file diff --git a/src/backends/tosaCommon/operatorMappings/ReshapeOperator.hpp b/src/backends/tosaCommon/operatorMappings/ReshapeOperator.hpp new file mode 100644 index 0000000000..4f363df052 --- /dev/null +++ b/src/backends/tosaCommon/operatorMappings/ReshapeOperator.hpp @@ -0,0 +1,20 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "TosaOperatorUtils.hpp" + +#include + +#include + +using namespace armnn; +using namespace tosa; + +TosaSerializationBasicBlock* ConvertReshapeToTosaOperator(const Layer* layer, + const std::vector& inputs, + const std::vector& outputs, + const ReshapeDescriptor* reshapeDescriptor); diff --git a/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp b/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp index 513db0c039..0711095a25 100644 --- a/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp +++ b/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp @@ -9,4 +9,5 @@ #include "ConstantOperator.hpp" #include "Conv2dOperator.hpp" #include "AvgPool2DIgnoreValueOperator.hpp" -#include "Pooling2DOperator.hpp" \ No newline at end of file +#include "Pooling2DOperator.hpp" +#include "ReshapeOperator.hpp" \ No newline at end of file diff --git a/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp b/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp index 176e4e1cfb..288966badd 100644 --- a/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp +++ b/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp @@ -59,28 +59,20 @@ inline std::vector GetTosaTensorShape(const TensorShape& shape) // Function that generates unique name using the layer type, input slot and layer guid. inline std::string GenerateUniqueName(const Layer& layer, uint32_t layerSlot) { - std::string name; std::string guid = std::to_string(layer.GetGuid()); std::string slotAndGuid = std::to_string(layerSlot) + "_" + guid; - LayerType layerType = layer.GetType(); - if (layerType == LayerType::Input) + switch (layer.GetType()) { - name = "input" + slotAndGuid; - } - else if (layerType == LayerType::Output) - { - name = "output" + slotAndGuid; - } - else if (layerType == LayerType::Constant) - { - name = "constant_" + guid; - } - else - { - name = "intermediate" + slotAndGuid; + case LayerType::Input: + return "input" + slotAndGuid; + case LayerType::Output: + return "output" + slotAndGuid; + case LayerType::Constant: + return "constant_" + guid; + default: + return "intermediate" + slotAndGuid; } - return name; } // Function to return unique int as a string to ensure uniqueness between all input, output and block names. @@ -90,6 +82,37 @@ inline std::string GetUniqueTosaMappingID() return std::to_string(++uniqueTosaMappingID); } +// Function to return Tosa DType as string. +inline std::string TosaDTypeToString(DType tosaDType) +{ + switch (tosaDType) + { + case DType_UNKNOWN: + return "DType_UNKNOWN"; + case DType_BOOL: + return "DType_BOOL"; + case DType_UINT8: + return "DType_UINT8"; + case DType_INT4: + return "DType_INT4"; + case DType_INT8: + return "DType_INT8"; + case DType_INT16: + return "DType_INT16"; + case DType_INT32: + return "DType_INT32"; + case DType_INT48: + return "DType_INT48"; + case DType_FP32: + return "DType_FP32"; + case DType_UINT16: + return "DType_UINT16"; + case DType_FP16: + return "DType_FP16"; + } + return ""; +} + // Function to return Tosa Op as string. inline std::string TosaOpToString(Op tosaOp) { diff --git a/src/backends/tosaCommon/test/AvgPool2DIgnoreValueChecker.hpp b/src/backends/tosaCommon/test/AvgPool2DIgnoreValueChecker.hpp index a38f66b466..6f57c4a61e 100644 --- a/src/backends/tosaCommon/test/AvgPool2DIgnoreValueChecker.hpp +++ b/src/backends/tosaCommon/test/AvgPool2DIgnoreValueChecker.hpp @@ -68,9 +68,11 @@ void VerifyAvgPool2DIgnoreValue(TosaSerializationBasicBlock* basicBlock, CHECK(padOp->GetAttributeType() == Attribute_PadAttribute); CHECK(padOp->GetOp() == Op_PAD); - VerifyTosaAttributeFromDescriptor(descriptor, - padOp->GetAttribute(), - LayerType::Pooling2d); + VerifyTosaAttribute(descriptor, + padOp->GetAttribute(), + inputShape[0], + outputShape[0], + LayerType::Pooling2d); // // Verify average pool operator second. @@ -115,9 +117,11 @@ void VerifyAvgPool2DIgnoreValue(TosaSerializationBasicBlock* basicBlock, CHECK(poolOp->GetAttributeType() == Attribute_PoolAttribute); CHECK(poolOp->GetOp() == Op_AVG_POOL2D); - VerifyTosaAttributeFromDescriptor(descriptor, - poolOp->GetAttribute(), - LayerType::Pooling2d, - 1); + VerifyTosaAttribute(descriptor, + poolOp->GetAttribute(), + inputShape[0], + outputShape[0], + LayerType::Pooling2d, + 1); } \ No newline at end of file diff --git a/src/backends/tosaCommon/test/OneToOneMappingTests.cpp b/src/backends/tosaCommon/test/OneToOneMappingTests.cpp index af9f9e26df..b1fa6847bc 100644 --- a/src/backends/tosaCommon/test/OneToOneMappingTests.cpp +++ b/src/backends/tosaCommon/test/OneToOneMappingTests.cpp @@ -79,7 +79,7 @@ TEST_CASE("GetTosaMappingFromLayer_ConstantLayer") std::vector> outputShape = {{ 1, 2, 4, 2 }}; std::vector data = GenerateRandomData(info.GetNumElements()); - armnn::ConstTensor constTensor(info, data); + ConstTensor constTensor(info, data); IConnectableLayer* constant = net->AddConstantLayer(constTensor, "constant"); IConnectableLayer* output = net->AddOutputLayer(0, "output"); @@ -95,7 +95,7 @@ TEST_CASE("GetTosaMappingFromLayer_ConstantLayer") TEST_CASE("GetTosaMapping_Conv2dLayer") { - armnn::Convolution2dDescriptor descriptor; + Convolution2dDescriptor descriptor; descriptor.m_PadLeft = 1; descriptor.m_PadRight = 1; descriptor.m_PadTop = 1; @@ -106,10 +106,10 @@ TEST_CASE("GetTosaMapping_Conv2dLayer") descriptor.m_DilationY = 2; descriptor.m_BiasEnabled = true; - const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32); - const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); - const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32, 0.0f, 0, true); - const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32, 0.0f, 0, true); + const TensorInfo inputInfo ({ 1, 5, 5, 1 }, DataType::Float32); + const TensorInfo outputInfo({ 1, 3, 3, 1 }, DataType::Float32); + const TensorInfo weightsInfo({ 1, 3, 3, 1 }, DataType::Float32, 0.0f, 0, true); + const TensorInfo biasesInfo ({ 1 }, DataType::Float32, 0.0f, 0, true); std::vector> inputShape = {{ 1, 5, 5, 1 }, { 1, 3, 3, 1 }, { 1 }}; std::vector> outputShape = {{ 1, 3, 3, 1 }}; @@ -131,7 +131,7 @@ TEST_CASE("GetTosaMappingFromLayer_Conv2dLayer") // Builds up the structure of the network. INetworkPtr net(INetwork::Create()); - armnn::Convolution2dDescriptor descriptor; + Convolution2dDescriptor descriptor; descriptor.m_PadLeft = 1; descriptor.m_PadRight = 1; descriptor.m_PadTop = 1; @@ -142,25 +142,25 @@ TEST_CASE("GetTosaMappingFromLayer_Conv2dLayer") descriptor.m_DilationY = 2; descriptor.m_BiasEnabled = true; - const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32); - const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); - const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32, 0.0f, 0, true); - const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32, 0.0f, 0, true); + const TensorInfo inputInfo ({ 1, 5, 5, 1 }, DataType::Float32); + const TensorInfo outputInfo({ 1, 3, 3, 1 }, DataType::Float32); + const TensorInfo weightsInfo({ 1, 3, 3, 1 }, DataType::Float32, 0.0f, 0, true); + const TensorInfo biasesInfo ({ 1 }, DataType::Float32, 0.0f, 0, true); std::vector> inputShape = {{ 1, 5, 5, 1 }}; std::vector> outputShape = {{ 1, 3, 3, 1 }}; std::vector weightsData = GenerateRandomData(weightsInfo.GetNumElements()); - armnn::ConstTensor weights(weightsInfo, weightsData); + ConstTensor weights(weightsInfo, weightsData); std::vector biasesData = GenerateRandomData(biasesInfo.GetNumElements()); - armnn::ConstTensor biases(biasesInfo, biasesData); + ConstTensor biases(biasesInfo, biasesData); - armnn::IConnectableLayer* const inputLayer = net->AddInputLayer(0, "input0"); - armnn::IConnectableLayer* const weightsLayer = net->AddConstantLayer(weights, "weights"); - armnn::IConnectableLayer* const biasesLayer = net->AddConstantLayer(biases, "biases"); - armnn::IConnectableLayer* const convLayer = net->AddConvolution2dLayer(descriptor, "conv2d"); - armnn::IConnectableLayer* const outputLayer = net->AddOutputLayer(0); + IConnectableLayer* const inputLayer = net->AddInputLayer(0, "input0"); + IConnectableLayer* const weightsLayer = net->AddConstantLayer(weights, "weights"); + IConnectableLayer* const biasesLayer = net->AddConstantLayer(biases, "biases"); + IConnectableLayer* const convLayer = net->AddConvolution2dLayer(descriptor, "conv2d"); + IConnectableLayer* const outputLayer = net->AddOutputLayer(0); inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); weightsLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(1)); @@ -179,18 +179,18 @@ TEST_CASE("GetTosaMappingFromLayer_Conv2dLayer") TEST_CASE("GetTosaMapping_MaxPool2DLayer") { - armnn::Pooling2dDescriptor descriptor; - descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; + Pooling2dDescriptor descriptor; + descriptor.m_PoolType = PoolingAlgorithm::Max; 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::Exclude; + descriptor.m_PaddingMethod = PaddingMethod::Exclude; - armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); - armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); + TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); + TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); std::vector> inputShape = {{ 1, 1, 4, 4 }}; std::vector> outputShape = {{ 1, 1, 3, 3 }}; @@ -209,30 +209,30 @@ TEST_CASE("GetTosaMappingFromLayer_MaxPool2DLayer") // Builds up the structure of the network. INetworkPtr net(INetwork::Create()); - armnn::Pooling2dDescriptor descriptor; - descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; + Pooling2dDescriptor descriptor; + descriptor.m_PoolType = PoolingAlgorithm::Max; 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::Exclude; + descriptor.m_PaddingMethod = PaddingMethod::Exclude; - IConnectableLayer* input0 = net->AddInputLayer(0, "input0"); - IConnectableLayer* pool = net->AddPooling2dLayer(descriptor, "pool"); - IConnectableLayer* output = net->AddOutputLayer(0, "output"); + IConnectableLayer* input = net->AddInputLayer(0, "input0"); + IConnectableLayer* pool = net->AddPooling2dLayer(descriptor, "pool"); + IConnectableLayer* output = net->AddOutputLayer(0, "output"); - input0->GetOutputSlot(0).Connect(pool->GetInputSlot(0)); + input->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); + TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); + TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); std::vector> inputShape = {{ 1, 1, 4, 4 }}; std::vector> outputShape = {{ 1, 1, 3, 3 }}; - input0->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); + input->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); pool->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); TosaSerializationBasicBlock* basicBlock = @@ -243,18 +243,18 @@ TEST_CASE("GetTosaMappingFromLayer_MaxPool2DLayer") TEST_CASE("GetTosaMapping_AvgPool2DLayer") { - armnn::Pooling2dDescriptor descriptor; - descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; + Pooling2dDescriptor descriptor; + descriptor.m_PoolType = 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::Exclude; + descriptor.m_PaddingMethod = PaddingMethod::Exclude; - armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); - armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); + TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); + TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); std::vector> inputShape = {{ 1, 1, 4, 4 }}; std::vector> outputShape = {{ 1, 1, 3, 3 }}; @@ -278,15 +278,15 @@ TEST_CASE("GetTosaMappingFromLayer_AvgPool2DLayer") // Builds up the structure of the network. INetworkPtr net(INetwork::Create()); - armnn::Pooling2dDescriptor descriptor; - descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; + Pooling2dDescriptor descriptor; + descriptor.m_PoolType = 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::Exclude; + descriptor.m_PaddingMethod = PaddingMethod::Exclude; IConnectableLayer* input0 = net->AddInputLayer(0, "input0"); IConnectableLayer* pool = net->AddPooling2dLayer(descriptor, "pool"); @@ -295,8 +295,8 @@ TEST_CASE("GetTosaMappingFromLayer_AvgPool2DLayer") 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); + TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32); + TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32); std::vector> inputShape = {{ 1, 1, 4, 4 }}; std::vector> outputShape = {{ 1, 1, 3, 3 }}; @@ -315,6 +315,66 @@ TEST_CASE("GetTosaMappingFromLayer_AvgPool2DLayer") LayerType::Pooling2d); } +TEST_CASE("GetTosaMapping_ReshapeLayer") +{ + TensorInfo inputInfo = TensorInfo({ 2, 3 }, DataType::Float32); + TensorInfo outputInfo = TensorInfo({ 6 }, DataType::Float32); + + std::vector> inputShape = {{ 2, 3 }}; + std::vector> outputShape = {{ 6 }}; + + ReshapeDescriptor descriptor; + descriptor.m_TargetShape = { 6 }; + + TosaSerializationBasicBlock* basicBlock = + GetTosaMapping(nullptr, LayerType::Reshape, {&inputInfo}, {&outputInfo}, descriptor); + AssertTosaOneToOneMappingBasicBlock(basicBlock, + inputShape, + outputShape, + Op_RESHAPE, + Attribute_ReshapeAttribute, + descriptor, + LayerType::Reshape); +} + +TEST_CASE("GetTosaMappingFromLayer_ReshapeLayer") +{ + IRuntime::CreationOptions options; + IRuntimePtr runtime(IRuntime::Create(options)); + + // Builds up the structure of the network. + INetworkPtr net(INetwork::Create()); + + ReshapeDescriptor descriptor; + descriptor.m_TargetShape = { 6 }; + + IConnectableLayer* input = net->AddInputLayer(0, "input"); + IConnectableLayer* reshape = net->AddReshapeLayer(descriptor, "reshape"); + IConnectableLayer* output = net->AddOutputLayer(0, "output"); + + input->GetOutputSlot(0).Connect(reshape->GetInputSlot(0)); + reshape->GetOutputSlot(0).Connect(output->GetInputSlot(0)); + + TensorInfo inputInfo = TensorInfo({ 2, 3 }, DataType::Float32); + TensorInfo outputInfo = TensorInfo({ 6 }, DataType::Float32); + + input->GetOutputSlot(0).SetTensorInfo(inputInfo); + reshape->GetOutputSlot(0).SetTensorInfo(outputInfo); + + std::vector> inputShape = {{ 2, 3 }}; + std::vector> outputShape = {{ 6 }}; + + TosaSerializationBasicBlock* basicBlock = + GetTosaMappingFromLayer(PolymorphicDowncast(reshape)); + AssertTosaOneToOneMappingBasicBlock(basicBlock, + inputShape, + outputShape, + Op_RESHAPE, + Attribute_ReshapeAttribute, + descriptor, + LayerType::Reshape); +} + TEST_CASE("GetTosaMapping_Unimplemented") { TosaSerializationBasicBlock* basicBlock = diff --git a/src/backends/tosaCommon/test/TosaTestUtils.hpp b/src/backends/tosaCommon/test/TosaTestUtils.hpp index dd63c0efdf..5c10a6d638 100644 --- a/src/backends/tosaCommon/test/TosaTestUtils.hpp +++ b/src/backends/tosaCommon/test/TosaTestUtils.hpp @@ -8,16 +8,20 @@ #include #include +#include #include +#include using namespace armnn; using namespace tosa; -inline void VerifyTosaAttributeFromDescriptor(const BaseDescriptor& descriptor, - const TosaAttributeBase* attribute, - LayerType type, - uint32_t mappingOpNumber = 0) +inline void VerifyTosaAttribute(const BaseDescriptor& descriptor, + const TosaAttributeBase* attribute, + std::vector inputShape, + std::vector outputShape, + LayerType type, + uint32_t mappingOpNumber = 0) { switch (type) { @@ -100,6 +104,25 @@ inline void VerifyTosaAttributeFromDescriptor(const BaseDescriptor& descriptor, CHECK(stride == poolAttribute.stride()); break; } + case LayerType::Reshape: + { + auto reshapeDesc = PolymorphicDowncast(&descriptor); + TosaReshapeAttribute reshapeAttribute(attribute); + std::vector shapeAttrib = reshapeAttribute.new_shape(); + + CHECK(GetTosaTensorShape(reshapeDesc->m_TargetShape) == shapeAttrib); + CHECK(outputShape == shapeAttrib); + + auto numInputElements = std::accumulate(std::begin(inputShape), + std::end(inputShape), + 1, + std::multiplies()); + auto numAttributeShapeElements = std::accumulate(std::begin(shapeAttrib), + std::end(shapeAttrib), + 1, + std::multiplies()); + CHECK(numInputElements == numAttributeShapeElements); + } default: break; } @@ -195,7 +218,22 @@ inline void AssertTosaOneToOneMappingBasicBlock(TosaSerializationBasicBlock* bas } } - VerifyTosaAttributeFromDescriptor(descriptor, - op->GetAttribute(), - type); + std::vector input = {}; + std::vector output = {}; + + if (!inputShape.empty()) + { + input = inputShape[0]; + } + + if (!outputShape.empty()) + { + output = outputShape[0]; + } + + VerifyTosaAttribute(descriptor, + op->GetAttribute(), + input, + output, + type); } \ No newline at end of file -- cgit v1.2.1