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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#include "MultiplicationLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <backends/WorkloadData.hpp>
#include <backends/WorkloadFactory.hpp>
namespace armnn
{
MultiplicationLayer::MultiplicationLayer(const char* name)
: Layer(2, 1, LayerType::Multiplication, name)
{
}
std::unique_ptr<IWorkload> MultiplicationLayer::CreateWorkload(const Graph& graph,
const IWorkloadFactory& factory) const
{
MultiplicationQueueDescriptor descriptor;
return factory.CreateMultiplication(descriptor, PrepInfoAndDesc(descriptor, graph));
}
MultiplicationLayer* MultiplicationLayer::Clone(Graph& graph) const
{
return CloneBase<MultiplicationLayer>(graph, GetName());
}
void MultiplicationLayer::ValidateTensorShapesFromInputs()
{
auto& input0 = GetInputSlot(0).GetConnection()->GetTensorInfo();
auto& input1 = GetInputSlot(1).GetConnection()->GetTensorInfo();
// Get the max of the inputs
BOOST_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());
unsigned int numDims = input0.GetNumDimensions();
std::vector<unsigned int> dims(numDims);
// validate inputs are broadcast compatible
#if !NDEBUG
for (unsigned int i = 0; i < numDims; i++)
{
unsigned int dim0 = input0.GetShape()[i];
unsigned int dim1 = input1.GetShape()[i];
if (dim0 != dim1)
{
BOOST_ASSERT_MSG(dim0 == 1 || dim1 == 1, "Dimensions should either match or one should be of size 1.");
}
}
#endif
for (unsigned int i = 0; i < numDims; i++)
{
unsigned int dim0 = input0.GetShape()[i];
unsigned int dim1 = input1.GetShape()[i];
dims[i] = std::max(dim0, dim1);
}
TensorShape outShape(numDims, dims.data());
ConditionalThrowIfNotEqual<LayerValidationException>(
"MultiplicationLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
GetOutputSlot(0).GetTensorInfo().GetShape(),
outShape);
}
} // namespace armnn
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