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//
// Copyright © 2023-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "TileLayer.hpp"
#include <armnn/backends/WorkloadFactory.hpp>
#include "layers/LayerCloneBase.hpp"
namespace armnn
{
TileLayer::TileLayer(const TileDescriptor ¶m, const char *name)
: LayerWithParameters(1, 1, LayerType::Tile, param, name)
{}
std::unique_ptr<IWorkload> TileLayer::CreateWorkload(const IWorkloadFactory &factory) const
{
TileQueueDescriptor descriptor;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::Tile, descriptor, PrepInfoAndDesc(descriptor));
}
TileLayer* TileLayer::Clone(armnn::Graph &graph) const
{
auto layer = CloneBase<TileLayer>(graph, m_Param, GetName());
return std::move(layer);
}
std::vector<TensorShape> TileLayer::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];
uint32_t numberOfDimensions = inputShape.GetNumDimensions();
std::vector<unsigned int> dimensionSizes;
dimensionSizes.reserve(numberOfDimensions);
// Check input shape and multiples have same length and multiply them together to get output shape
if(numberOfDimensions == m_Param.m_Multiples.size())
{
for(uint32_t i = 0; i < numberOfDimensions; ++i)
{
dimensionSizes.emplace_back(inputShape[i] * m_Param.m_Multiples[i]);
}
}
else
{
throw LayerValidationException("TileLayer: input rank and multiples length are different.");
}
return std::vector<TensorShape>({TensorShape({numberOfDimensions, dimensionSizes.data()})});
}
void TileLayer::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, "TileLayer");
}
}
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