// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include "ElementwiseBaseLayer.hpp" #include "InternalTypes.hpp" #include "armnn/Exceptions.hpp" #include #include namespace armnn { ElementwiseBaseLayer::ElementwiseBaseLayer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char* name) : Layer(numInputSlots, numOutputSlots, type, name) { } std::vector ElementwiseBaseLayer::InferOutputShapes(const std::vector& inputShapes) const { BOOST_ASSERT(inputShapes.size() == 2); auto& input0 = inputShapes[0]; auto& input1 = inputShapes[1]; // Get the max of the inputs. BOOST_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions()); unsigned int numDims = input0.GetNumDimensions(); std::vector dims(numDims); for (unsigned int i = 0; i < numDims; i++) { unsigned int dim0 = input0[i]; unsigned int dim1 = input1[i]; #if !NDEBUG // Validate inputs are broadcast compatible. BOOST_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1, "Dimensions should either match or one should be of size 1."); #endif dims[i] = std::max(dim0, dim1); } return std::vector({ TensorShape(numDims, dims.data()) }); } void ElementwiseBaseLayer::ValidateTensorShapesFromInputs() { VerifyLayerConnections(2, CHECK_LOCATION()); auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(), GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape() }); BOOST_ASSERT(inferredShapes.size() == 1); std::string msg = GetLayerTypeAsCString(GetType()); msg += "Layer: TensorShape set on OutputSlot[0] does not match the inferred shape."; ConditionalThrowIfNotEqual(msg, GetOutputSlot(0).GetTensorInfo().GetShape(), inferredShapes[0]); } } // namespace armnn