| // |
| // Copyright © 2019-2024 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #include "InstanceNormalizationLayer.hpp" |
| |
| #include "LayerCloneBase.hpp" |
| |
| #include <armnn/TypesUtils.hpp> |
| #include <armnn/backends/WorkloadData.hpp> |
| #include <armnn/backends/WorkloadFactory.hpp> |
| |
| namespace armnn |
| { |
| |
| InstanceNormalizationLayer::InstanceNormalizationLayer(const InstanceNormalizationDescriptor& param, const char* name) |
| : LayerWithParameters(1, 1, LayerType::InstanceNormalization, param, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> InstanceNormalizationLayer::CreateWorkload(const IWorkloadFactory& factory) const |
| { |
| InstanceNormalizationQueueDescriptor descriptor; |
| SetAdditionalInfo(descriptor); |
| |
| return factory.CreateWorkload(LayerType::InstanceNormalization, descriptor, PrepInfoAndDesc(descriptor)); |
| } |
| |
| InstanceNormalizationLayer* InstanceNormalizationLayer::Clone(Graph& graph) const |
| { |
| return CloneBase<InstanceNormalizationLayer>(graph, m_Param, GetName()); |
| } |
| |
| void InstanceNormalizationLayer::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, "InstanceNormalizationLayer"); |
| } |
| |
| void InstanceNormalizationLayer::ExecuteStrategy(IStrategy& strategy) const |
| { |
| strategy.ExecuteStrategy(this, GetParameters(), {}, GetName()); |
| } |
| |
| } // namespace armnn |