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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "BatchNormalizationLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <backends/CpuTensorHandle.hpp>
#include <backends/WorkloadFactory.hpp>
namespace armnn
{
BatchNormalizationLayer::BatchNormalizationLayer(const armnn::BatchNormalizationDescriptor& param, const char* name)
: LayerWithParameters(1, 1, LayerType::BatchNormalization, param, name)
{
}
std::unique_ptr<IWorkload> BatchNormalizationLayer::CreateWorkload(const Graph& graph,
const IWorkloadFactory& factory) const
{
// on this level constant data should not be released..
BOOST_ASSERT_MSG(m_Mean != nullptr, "BatchNormalizationLayer: Mean data should not be null.");
BOOST_ASSERT_MSG(m_Variance != nullptr, "BatchNormalizationLayer: Variance data should not be null.");
BOOST_ASSERT_MSG(m_Beta != nullptr, "BatchNormalizationLayer: Beta data should not be null.");
BOOST_ASSERT_MSG(m_Gamma != nullptr, "BatchNormalizationLayer: Gamma data should not be null.");
BatchNormalizationQueueDescriptor descriptor;
descriptor.m_Mean = m_Mean.get();
descriptor.m_Variance = m_Variance.get();
descriptor.m_Beta = m_Beta.get();
descriptor.m_Gamma = m_Gamma.get();
return factory.CreateBatchNormalization(descriptor, PrepInfoAndDesc(descriptor, graph));
}
BatchNormalizationLayer* BatchNormalizationLayer::Clone(Graph& graph) const
{
auto layer = CloneBase<BatchNormalizationLayer>(graph, m_Param, GetName());
layer->m_Mean = m_Mean ? std::make_unique<ScopedCpuTensorHandle>(*m_Mean) : nullptr;
layer->m_Variance = m_Variance ? std::make_unique<ScopedCpuTensorHandle>(*m_Variance) : nullptr;
layer->m_Beta = m_Beta ? std::make_unique<ScopedCpuTensorHandle>(*m_Beta) : nullptr;
layer->m_Gamma = m_Gamma ? std::make_unique<ScopedCpuTensorHandle>(*m_Gamma) : nullptr;
return std::move(layer);
}
void BatchNormalizationLayer::ValidateTensorShapesFromInputs()
{
VerifyLayerConnections(1, CHECK_LOCATION());
auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() });
BOOST_ASSERT(inferredShapes.size() == 1);
ConditionalThrowIfNotEqual<LayerValidationException>(
"BatchNormalizationLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
GetOutputSlot(0).GetTensorInfo().GetShape(),
inferredShapes[0]);
}
Layer::ConstantTensors BatchNormalizationLayer::GetConstantTensorsByRef()
{
return {m_Mean, m_Variance, m_Beta, m_Gamma};
}
} // namespace armnn
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