blob: d810bef9dd4ee29e7514030a812ae8787f95d9c3 [file] [log] [blame]
//
// Copyright © 2021-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ShapeLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <armnn/utility/NumericCast.hpp>
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
namespace armnn
{
ShapeLayer::ShapeLayer(const char* name)
: Layer(1, 1, LayerType::Shape, name)
{
}
std::unique_ptr<IWorkload> ShapeLayer::CreateWorkload(const IWorkloadFactory& factory) const
{
ShapeQueueDescriptor descriptor;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::Shape, descriptor, PrepInfoAndDesc(descriptor));
}
ShapeLayer* ShapeLayer::Clone(Graph& graph) const
{
return CloneBase<ShapeLayer>(graph, GetName());
}
void ShapeLayer::ValidateTensorShapesFromInputs()
{
VerifyLayerConnections(1, CHECK_LOCATION());
const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
auto inferredShape = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape() });
if (inferredShape.size() != 1)
{
throw armnn::LayerValidationException("inferredShape has "
+ std::to_string(inferredShape.size()) +
" elements - should only have 1.");
}
ValidateAndCopyShape(outputShape, inferredShape[0], m_ShapeInferenceMethod, "ShapeLayer");
}
std::vector<TensorShape> ShapeLayer::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\".");
}
TensorShape outputShape({ inputShapes[0].GetNumDimensions()} );
return std::vector<TensorShape>({ outputShape });
}
void ShapeLayer::ExecuteStrategy(IStrategy& strategy) const
{
strategy.ExecuteStrategy(this, BaseDescriptor(), {}, GetName());
}
} // namespace armnn