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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "SliceOperator.hpp"
TosaSerializationBasicBlock* ConvertSliceToTosaOperator(const Layer* layer,
const std::vector<const TensorInfo*>& inputs,
const std::vector<const TensorInfo*>& outputs,
const SliceDescriptor* sliceDescriptor)
{
std::string inputName = std::string("input0_");
std::string outputName = std::string("output0_");
std::string blockName = std::string("Op_SLICE_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 tensor names.
Layer& connectedLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
inputName = GenerateUniqueName(connectedLayer, 0);
// Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}
std::vector<int32_t> begin(sliceDescriptor->m_Begin.begin(), sliceDescriptor->m_Begin.end());
std::vector<int32_t> size(sliceDescriptor->m_Size.begin(), sliceDescriptor->m_Size.end());
TosaSliceAttribute attribute(begin, size);
auto* op = new TosaSerializationOperator(Op_SLICE,
Attribute_SliceAttribute,
&attribute,
{inputName},
{outputName});
std::vector<TosaSerializationTensor*> tensors;
// 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(inputName.find("input0_") != std::string::npos)
{
std::vector<int32_t> inputShape = GetTosaTensorShape(inputs[0]->GetShape());
DType inputDType = ArmNNToDType(inputs[0]->GetDataType());
tensors.push_back(new TosaSerializationTensor(inputName, inputShape, inputDType, {}));
}
std::vector<int32_t> outputShape = GetTosaTensorShape(outputs[0]->GetShape());
DType outputDType = ArmNNToDType(outputs[0]->GetDataType());
tensors.push_back(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
mainName, // region name
{op}, // operators
tensors, // tensors
{inputName}, // inputs
{outputName}); // outputs
}
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