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//
// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "Pooling2dLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <armnnUtils/DataLayoutIndexed.hpp>
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
using namespace armnnUtils;
namespace armnn
{
Pooling2dLayer::Pooling2dLayer(const Pooling2dDescriptor& param, const char* name)
: LayerWithParameters(1, 1, LayerType::Pooling2d, param, name)
{
}
std::unique_ptr<IWorkload> Pooling2dLayer::CreateWorkload(const IWorkloadFactory& factory) const
{
Pooling2dQueueDescriptor descriptor;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::Pooling2d, descriptor, PrepInfoAndDesc(descriptor));
}
Pooling2dLayer* Pooling2dLayer::Clone(Graph& graph) const
{
return CloneBase<Pooling2dLayer>(graph, m_Param, GetName());
}
std::vector<TensorShape> Pooling2dLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
{
if (inputShapes.size() != 1)
{
throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
"\" - should be \"1\".");
}
const TensorShape& inputShape = inputShapes[0];
const DataLayoutIndexed dimensionIndices = m_Param.m_DataLayout;
// If we support multiple batch dimensions in the future, then this assert will need to change.
if (inputShape.GetNumDimensions() != 4)
{
throw armnn::Exception("Pooling2dLayer will always have 4D input.");
}
unsigned int inWidth = inputShape[dimensionIndices.GetWidthIndex()];
unsigned int inHeight = inputShape[dimensionIndices.GetHeightIndex()];
unsigned int inChannels = inputShape[dimensionIndices.GetChannelsIndex()];
unsigned int inBatchSize = inputShape[0];
bool isGlobalPooling = (m_Param.m_StrideX==0 && m_Param.m_StrideY==0);
unsigned int outWidth = 1;
unsigned int outHeight = 1;
if (!isGlobalPooling)
{
if (!m_Param.m_StrideX || !m_Param.m_StrideY)
{
throw armnn::Exception("Stride can only be zero when performing global pooling");
}
auto CalcSize = [](auto inSize, auto lowPad, auto highPad, auto poolSize, auto stride, auto outputShapeRounding)
{
unsigned int readSize = inSize + lowPad + highPad - poolSize;
float div = static_cast<float>(readSize) / static_cast<float>(stride);
unsigned int size = 0;
switch (outputShapeRounding)
{
case OutputShapeRounding::Ceiling:
size = static_cast<unsigned int>(ceil(div)) + 1;
break;
case OutputShapeRounding ::Floor:
size = static_cast<unsigned int>(floor(div)) + 1;
break;
default:
throw armnn::Exception("Unsupported Output Shape Rounding");
}
// MakeS sure that border operations will start from inside the input and not the padded area.
// This is what CL does...
if ((size - 1)*stride >= inSize + lowPad)
{
--size;
}
return size;
};
outWidth = CalcSize(inWidth, m_Param.m_PadLeft, m_Param.m_PadRight, m_Param.m_PoolWidth, m_Param.m_StrideX,
m_Param.m_OutputShapeRounding);
outHeight = CalcSize(inHeight, m_Param.m_PadTop, m_Param.m_PadBottom, m_Param.m_PoolHeight, m_Param.m_StrideY,
m_Param.m_OutputShapeRounding);
}
unsigned int outChannels = inChannels;
unsigned int outBatchSize = inBatchSize;
TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
TensorShape( { outBatchSize, outHeight, outWidth, outChannels } ) :
TensorShape( { outBatchSize, outChannels, outHeight, outWidth });
return std::vector<TensorShape>({ tensorShape });
}
void Pooling2dLayer::ValidateTensorShapesFromInputs()
{
VerifyLayerConnections(1, CHECK_LOCATION());
const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape() });
if (inferredShapes.size() != 1)
{
throw armnn::LayerValidationException("inferredShapes has "
+ std::to_string(inferredShapes.size()) +
" elements - should only have 1.");
}
ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "Pooling2dLayer");
}
void Pooling2dLayer::ExecuteStrategy(IStrategy& strategy) const
{
strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
} // namespace armnn
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