| // |
| // Copyright © 2022 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "Pooling2DOperator.hpp" |
| |
| TosaSerializationBasicBlock* ConvertAvgPool2DIgnoreValueToTosaOperator(const Layer* layer, |
| const std::vector<const TensorInfo*>& inputs, |
| const std::vector<const TensorInfo*>& outputs, |
| const Pooling2dDescriptor* poolDescriptor) |
| { |
| std::string padInputName = std::string("input0_"); |
| std::string padOutputName = std::string("intermediate0_") + GetUniqueTosaMappingID(); |
| std::string poolOutputName = std::string("output0_"); |
| std::string blockName = std::string("Op_AVG_POOL2D_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 tensors names. |
| Layer& connectedInputLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer(); |
| padInputName = GenerateUniqueName(connectedInputLayer, 0); |
| |
| // Determine unique output tensor name. |
| poolOutputName = GenerateUniqueOutputName(*layer, 0); |
| } |
| |
| std::vector<int> paddings; |
| if (poolDescriptor->m_DataLayout == DataLayout::NHWC) |
| { |
| paddings = {0, |
| 0, |
| static_cast<int>(poolDescriptor->m_PadTop), |
| static_cast<int>(poolDescriptor->m_PadBottom), |
| static_cast<int>(poolDescriptor->m_PadLeft), |
| static_cast<int>(poolDescriptor->m_PadRight), |
| 0, |
| 0 |
| }; |
| } |
| else |
| { |
| paddings = {0, |
| 0, |
| 0, |
| 0, |
| static_cast<int>(poolDescriptor->m_PadTop), |
| static_cast<int>(poolDescriptor->m_PadBottom), |
| static_cast<int>(poolDescriptor->m_PadLeft), |
| static_cast<int>(poolDescriptor->m_PadRight) |
| }; |
| } |
| |
| TosaPadAttribute padAttribute(paddings, 0, 0.0f); |
| auto* opPad = new TosaSerializationOperator(Op_PAD, |
| Attribute_PadAttribute, |
| &padAttribute, |
| {padInputName}, |
| {padOutputName}); |
| |
| std::vector<int> pad = {0, 0, 0, 0}; |
| std::vector<int> kernel = {static_cast<int>(poolDescriptor->m_PoolHeight), |
| static_cast<int>(poolDescriptor->m_PoolWidth)}; |
| std::vector<int> stride = {static_cast<int>(poolDescriptor->m_StrideY), |
| static_cast<int>(poolDescriptor->m_StrideX)}; |
| TosaPoolAttribute poolAttribute(pad, kernel, stride, 0, 0, ArmNNToDType(inputs[0]->GetDataType())); |
| |
| auto* opPool = new TosaSerializationOperator(Op_AVG_POOL2D, |
| Attribute_PoolAttribute, |
| &poolAttribute, |
| {padOutputName}, |
| {poolOutputName}); |
| |
| std::vector<TosaSerializationTensor*> tensors; |
| |
| std::vector<int32_t> inputShape = GetTosaTensorShape(inputs[0]->GetShape()); |
| DType inputDType = ArmNNToDType(inputs[0]->GetDataType()); |
| |
| // Only add input tensors if connected layer is an input layer. |
| // As intermediate or constant tensors will be created separately. |
| // There also can't be duplicate tensor. |
| if(padInputName.find("input0_") != std::string::npos) |
| { |
| tensors.push_back(new TosaSerializationTensor(padInputName, inputShape, inputDType, {})); |
| } |
| |
| std::vector<int32_t> outputShape = GetTosaTensorShape(outputs[0]->GetShape()); |
| DType outputDType = ArmNNToDType(outputs[0]->GetDataType()); |
| |
| std::vector<int32_t> intermediateShape; |
| if (poolDescriptor->m_DataLayout == DataLayout::NHWC) |
| { |
| intermediateShape = {inputShape[0], |
| inputShape[1] + paddings[2] + paddings[3], |
| inputShape[2] + paddings[4] + paddings[5], |
| inputShape[3]}; |
| } |
| else |
| { |
| intermediateShape = {inputShape[0], |
| inputShape[1], |
| inputShape[2] + paddings[4] + paddings[5], |
| inputShape[3] + paddings[6] + paddings[7]}; |
| } |
| |
| tensors.push_back(new TosaSerializationTensor(padOutputName, intermediateShape, inputDType, {})); |
| tensors.push_back(new TosaSerializationTensor(poolOutputName, 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 |
| mainName, // region name |
| {opPad, opPool}, // operators |
| tensors, // tensors |
| {padInputName}, // inputs |
| {poolOutputName}); // outputs |
| } |