| // |
| // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "LogicalBinaryLayer.hpp" |
| |
| #include "LayerCloneBase.hpp" |
| |
| #include <armnn/backends/WorkloadData.hpp> |
| #include <armnn/backends/WorkloadFactory.hpp> |
| |
| #include <algorithm> |
| |
| namespace armnn |
| { |
| |
| LogicalBinaryLayer::LogicalBinaryLayer(const LogicalBinaryDescriptor& param, const char* name) |
| : LayerWithParameters(2, 1, LayerType::LogicalBinary, param, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> LogicalBinaryLayer::CreateWorkload(const IWorkloadFactory& factory) const |
| { |
| LogicalBinaryQueueDescriptor descriptor; |
| return factory.CreateWorkload(LayerType::LogicalBinary, descriptor, PrepInfoAndDesc(descriptor)); |
| } |
| |
| LogicalBinaryLayer* LogicalBinaryLayer::Clone(Graph& graph) const |
| { |
| return CloneBase<LogicalBinaryLayer>(graph, m_Param, GetName()); |
| } |
| |
| std::vector<TensorShape> LogicalBinaryLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const |
| { |
| ARMNN_ASSERT(inputShapes.size() == 2); |
| const TensorShape& input0 = inputShapes[0]; |
| const TensorShape& input1 = inputShapes[1]; |
| |
| ARMNN_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions()); |
| unsigned int numDims = input0.GetNumDimensions(); |
| |
| std::vector<unsigned int> dims(numDims); |
| for (unsigned int i = 0; i < numDims; i++) |
| { |
| unsigned int dim0 = input0[i]; |
| unsigned int dim1 = input1[i]; |
| |
| ARMNN_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1, |
| "Dimensions should either match or one should be of size 1."); |
| |
| dims[i] = std::max(dim0, dim1); |
| } |
| |
| return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) }); |
| } |
| |
| void LogicalBinaryLayer::ValidateTensorShapesFromInputs() |
| { |
| VerifyLayerConnections(2, CHECK_LOCATION()); |
| |
| const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape(); |
| |
| VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod); |
| |
| std::vector<TensorShape> inferredShapes = InferOutputShapes({ |
| GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(), |
| GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape() |
| }); |
| ARMNN_ASSERT(inferredShapes.size() == 1); |
| |
| ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LogicalBinaryLayer"); |
| } |
| |
| ARMNN_NO_DEPRECATE_WARN_BEGIN |
| void LogicalBinaryLayer::Accept(ILayerVisitor& visitor) const |
| { |
| visitor.VisitLogicalBinaryLayer(this, GetParameters(), GetName()); |
| } |
| ARMNN_NO_DEPRECATE_WARN_END |
| |
| } // namespace armnn |