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//
// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ScatterNdLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
namespace armnn
{
ScatterNdLayer::ScatterNdLayer(const ScatterNdDescriptor ¶m, const char* name)
: LayerWithParameters(3, 1, LayerType::ScatterNd, param, name)
{
}
std::unique_ptr<IWorkload> ScatterNdLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const
{
ScatterNdQueueDescriptor descriptor;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::ScatterNd, descriptor, PrepInfoAndDesc(descriptor));
}
ScatterNdLayer* ScatterNdLayer::Clone(Graph& graph) const
{
auto layer = CloneBase<ScatterNdLayer>(graph, m_Param, GetName());
return std::move(layer);
}
std::vector<TensorShape> ScatterNdLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
{
const auto inputDims = inputShapes[0].GetNumDimensions();
std::vector<unsigned int> dimSizes(inputDims);
for (unsigned i = 0; i < inputDims; ++i)
{
dimSizes[i] = inputShapes[0][i];
}
TensorShape outputShape({ inputDims, dimSizes.data() });
return std::vector<TensorShape>({ outputShape });
}
void ScatterNdLayer::ValidateTensorShapesFromInputs()
{
VerifyLayerConnections(3, CHECK_LOCATION());
const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
if (m_Param.m_InputEnabled)
{
std::vector<TensorShape> inferredShapes = InferOutputShapes(
{GetInputSlot(0).GetTensorInfo().GetShape(),
GetInputSlot(1).GetTensorInfo().GetShape(),
GetInputSlot(2).GetTensorInfo().GetShape()});
if (inferredShapes.size() != 1) {
throw armnn::LayerValidationException("inferredShape has " +
std::to_string(inferredShapes.size()) +
" elements - should only have 1.");
}
ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "ScatterLayer");
}
else
{
// No input tensor, only shape provided via input slot
// In this case, we cannot validate the output shape from the input shape, but we can
// validate that the dimensions of shape and output tensor matched
unsigned int shapeDims = GetInputSlot(0).GetTensorInfo().GetShape().GetNumElements();
unsigned int outputDims = GetOutputSlot(0).GetTensorInfo().GetNumDimensions();
if (shapeDims != outputDims)
{
throw armnn::LayerValidationException("shape dimension " +
std::to_string(shapeDims) +
" and output dimension " +
std::to_string(outputDims) +
" are not matched.");
}
}
}
} // namespace armnn
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