diff options
author | surmeh01 <surabhi.mehta@arm.com> | 2018-05-18 16:31:43 +0100 |
---|---|---|
committer | telsoa01 <telmo.soares@arm.com> | 2018-05-23 13:09:07 +0100 |
commit | 3537c2ca7ebf31c1673b9ec2bb0c17b0406bbae0 (patch) | |
tree | 5950603ad78ec3fe56fb31ddc7f4d52a19f5bc60 /src/armnn/layers/FullyConnectedLayer.cpp | |
parent | bceff2fb3fc68bb0aa88b886900c34b77340c826 (diff) | |
download | armnn-3537c2ca7ebf31c1673b9ec2bb0c17b0406bbae0.tar.gz |
Release 18.05
Diffstat (limited to 'src/armnn/layers/FullyConnectedLayer.cpp')
-rw-r--r-- | src/armnn/layers/FullyConnectedLayer.cpp | 69 |
1 files changed, 69 insertions, 0 deletions
diff --git a/src/armnn/layers/FullyConnectedLayer.cpp b/src/armnn/layers/FullyConnectedLayer.cpp new file mode 100644 index 0000000000..1597e8c2c3 --- /dev/null +++ b/src/armnn/layers/FullyConnectedLayer.cpp @@ -0,0 +1,69 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// See LICENSE file in the project root for full license information. +// +#include "FullyConnectedLayer.hpp" + +#include "LayerCloneBase.hpp" + +#include <armnn/TypesUtils.hpp> +#include <backends/CpuTensorHandle.hpp> +#include <backends/WorkloadData.hpp> +#include <backends/WorkloadFactory.hpp> + +namespace armnn +{ + +FullyConnectedLayer::FullyConnectedLayer(const FullyConnectedDescriptor& param, const char* name) + : LayerWithParameters(1, 1, LayerType::FullyConnected, param, name) +{ +} + +std::unique_ptr<IWorkload> FullyConnectedLayer::CreateWorkload(const Graph& graph, + const IWorkloadFactory& factory) const +{ + FullyConnectedQueueDescriptor descriptor; + + descriptor.m_Weight = m_Weight.get(); + if (m_Param.m_BiasEnabled) + { + descriptor.m_Bias = m_Bias.get(); + } + return factory.CreateFullyConnected(descriptor, PrepInfoAndDesc(descriptor, graph)); +} + +FullyConnectedLayer* FullyConnectedLayer::Clone(Graph& graph) const +{ + auto layer = CloneBase<FullyConnectedLayer>(graph, m_Param, GetName()); + + layer->m_Weight = m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr; + if (layer->m_Param.m_BiasEnabled) + { + layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr; + } + + return std::move(layer); +} + +void FullyConnectedLayer::ValidateTensorShapesFromInputs() +{ + ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection() != nullptr, + "FullyConnectedLayer: InputSlot must be connected to an OutputSlot"); + ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection()->IsTensorInfoSet(), + "FullyConnectedLayer: TensorInfo must be set on connected OutputSlot."); + + + TensorShape const& weightShape = m_Weight->GetTensorInfo().GetShape(); + + // output for FC is [1, w[1]] + unsigned int batches = GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape()[0]; + unsigned int dimIdx = m_Param.m_TransposeWeightMatrix ? 0 : 1; + TensorShape outShape({batches, weightShape[dimIdx]}); + + ConditionalThrowIfNotEqual<LayerValidationException>( + "FullyConnectedLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", + GetOutputSlot(0).GetTensorInfo().GetShape(), + outShape); +} + +} // namespace armnn |