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//
// Copyright © 2022-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "Pooling2DOperator.hpp"
TosaSerializationBasicBlock* ConvertPooling2DToTosaOperator(const Layer* layer,
const std::vector<const TensorInfo*>& inputs,
const std::vector<const TensorInfo*>& outputs,
const Pooling2dDescriptor* poolDescriptor)
{
std::string poolType = (poolDescriptor->m_PoolType == PoolingAlgorithm::Max) ? "Op_MAX" : "Op_AVG";
Op opcode = (poolDescriptor->m_PoolType == PoolingAlgorithm::Max) ? Op_MAX_POOL2D : Op_AVG_POOL2D;
std::string input0Name = std::string("input_");
std::string outputName = std::string("output0_");
std::string blockName = std::string("Op_") + poolType + std::string("_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)
{
input0Name = GenerateUniqueInputName(layer->GetInputSlot(0));
outputName = GenerateUniqueOutputName(*layer);
}
std::vector<int> pad = {static_cast<int>(poolDescriptor->m_PadTop),
static_cast<int>(poolDescriptor->m_PadBottom),
static_cast<int>(poolDescriptor->m_PadLeft),
static_cast<int>(poolDescriptor->m_PadRight)};
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 attribute(pad, kernel, stride, 0, 0, ArmNNToDType(inputs[0]->GetDataType()));
auto* op = new TosaSerializationOperator(opcode,
Attribute_PoolAttribute,
&attribute,
{input0Name},
{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(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
}
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