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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "AdditionOperator.hpp"
TosaSerializationBasicBlock* ConvertAdditionToTosaOperator(const Layer* layer,
const std::vector<const TensorInfo*>& inputs,
const std::vector<const TensorInfo*>& outputs)
{
std::string input0Name = std::string("input0_");
std::string input1Name = std::string("input1_");
std::string outputName = std::string("output0_");
std::string blockName = std::string("Op_ADD_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& connectedLayer0 = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
input0Name = GenerateUniqueName(connectedLayer0, 0);
Layer& connectedLayer1 = layer->GetInputSlot(1).GetConnectedOutputSlot()->GetOwningLayer();
input1Name = GenerateUniqueName(connectedLayer1, 1);
// Get the layer connected to the output slot and determine unique layer name.
Layer& connectedOutputLayer = layer->GetOutputSlot().GetConnection(0)->GetOwningLayer();
outputName = GenerateUniqueName(connectedOutputLayer, 0);
}
auto* op = new TosaSerializationOperator(Op_ADD,
Attribute_NONE,
nullptr,
{input0Name, input1Name},
{outputName});
std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape());
DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType());
std::vector<int32_t> inputShape1 = GetTosaTensorShape(inputs[1]->GetShape());
DType inputDType1 = ArmNNToDType(inputs[1]->GetDataType());
std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape());
DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType());
auto* inputTensor0 = new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {});
auto* inputTensor1 = new TosaSerializationTensor(input1Name, inputShape1, inputDType1, {});
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
return new TosaSerializationBasicBlock(blockName, // name
{op}, // operators
{inputTensor0, inputTensor1, outputTensor0}, // tensors
{input0Name, input1Name}, // inputs
{outputName}); // outputs
}
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