blob: 761814176d57bfb9908f0a2c5a302d0c30a2bfb5 [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ElementwiseBaseLayer.hpp"
#include "InternalTypes.hpp"
#include "armnn/Exceptions.hpp"
#include <armnn/TypesUtils.hpp>
#include <boost/assert.hpp>
namespace armnn
{
ElementwiseBaseLayer::ElementwiseBaseLayer(unsigned int numInputSlots, unsigned int numOutputSlots,
LayerType type, const char* name)
: Layer(numInputSlots, numOutputSlots, type, name)
{
}
std::vector<TensorShape> ElementwiseBaseLayer::InferOutputShapes(const std::vector<TensorShape>& 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<unsigned int> 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>({ 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<LayerValidationException>(msg,
GetOutputSlot(0).GetTensorInfo().GetShape(),
inferredShapes[0]);
}
} // namespace armnn