| // |
| // Copyright © 2023-2024 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ElementwiseUnaryOperator.hpp" |
| |
| TosaSerializationBasicBlock* ConvertElementwiseUnaryOperator(const Layer* layer, |
| const std::vector<const TensorInfo*>& inputs, |
| const std::vector<const TensorInfo*>& outputs, |
| const ElementwiseUnaryDescriptor* unaryDescriptor) |
| { |
| std::string input0Name = std::string("input_"); |
| std::string outputName = std::string("output0_"); |
| std::string blockName = std::string("Op_ELEMENTWISEUNARY_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) |
| { |
| input0Name = GenerateUniqueInputName(layer->GetInputSlot(0)); |
| outputName = GenerateUniqueOutputName(*layer); |
| } |
| |
| TosaSerializationOperator* op = nullptr; |
| switch(unaryDescriptor->m_Operation) |
| { |
| case UnaryOperation::Rsqrt: |
| { |
| op = new TosaSerializationOperator(tosa::Op_RSQRT, |
| Attribute_NONE, |
| nullptr, |
| {input0Name}, |
| {outputName}); |
| blockName = std::string("Op_RSQRT_block_") + GetUniqueTosaMappingID(); |
| break; |
| } |
| default: |
| throw armnn::Exception("ConvertElementwiseUnaryToTosaOperator: Unsupported layer type."); |
| } |
| |
| std::vector<TosaSerializationTensor*> tensors; |
| // Only add input tensor if connected layer is an input layer. |
| // As intermediate or constant tensors will be created separately. |
| // There also can't be duplicate tensor. |
| if(input0Name.find("input_") != std::string::npos) |
| { |
| std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape()); |
| DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType()); |
| tensors.push_back(new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {})); |
| } |
| |
| std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape()); |
| DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType()); |
| |
| tensors.push_back(new TosaSerializationTensor(outputName, outputShape0, outputDType0, {})); |
| |
| // 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 |
| {op}, // operators |
| tensors, // tensors |
| {input0Name}, // inputs |
| {outputName}); // outputs |
| } |