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author | Conor Kennedy <conor.kennedy@arm.com> | 2018-12-21 14:38:36 +0000 |
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committer | Les Bell <les.bell@arm.com> | 2018-12-24 09:33:39 +0000 |
commit | 35052ae3f44d24cd71f437a2011c5032d34c94a7 (patch) | |
tree | 21cdc0f077606f80713f75c6eaeace2adcd4bb20 /src/armnn/layers/LstmLayer.hpp | |
parent | a06bf31afabfb84e60740ea3219406ab13c8e6a6 (diff) | |
download | armnn-35052ae3f44d24cd71f437a2011c5032d34c94a7.tar.gz |
IVGCVSW-59 Add documentation to the public API
* Add documentation to the Descriptors
* Add documentation to the layers
Change-Id: I5e0849753903565227fd47d329a600fd90b2feb9
Diffstat (limited to 'src/armnn/layers/LstmLayer.hpp')
-rw-r--r-- | src/armnn/layers/LstmLayer.hpp | 39 |
1 files changed, 39 insertions, 0 deletions
diff --git a/src/armnn/layers/LstmLayer.hpp b/src/armnn/layers/LstmLayer.hpp index 247fec389d..6004d9666b 100644 --- a/src/armnn/layers/LstmLayer.hpp +++ b/src/armnn/layers/LstmLayer.hpp @@ -13,37 +13,55 @@ class ScopedCpuTensorHandle; struct LstmOptCifgParameters { + /// A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_InputToInputWeights; + /// A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToInputWeights; + /// A unique pointer to represent 1D weights tensor with dimensions [num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_CellToInputWeights; + /// A unique pointer to represent 1D weights tensor with dimensions [num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_InputGateBias; }; struct LstmOptProjectionParameters { + /// A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_ProjectionWeights; + /// A unique pointer to represent 1D weights tensor with dimensions [output_size]. std::unique_ptr<ScopedCpuTensorHandle> m_ProjectionBias; }; struct LstmOptPeepholeParameters { + /// A unique pointer to represent 1D weights tensor with dimensions [num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_CellToForgetWeights; + /// A unique pointer to represent 1D weights tensor with dimensions [num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_CellToOutputWeights; }; struct LstmBasicParameters { + /// A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_InputToForgetWeights; + /// A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_InputToCellWeights; + /// A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_InputToOutputWeights; + /// A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToForgetWeights; + /// A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToCellWeights; + /// A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToOutputWeights; + /// A unique pointer to represent 1D weights tensor with dimensions [num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_ForgetGateBias; + /// A unique pointer to represent 1D weights tensor with dimensions [num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_CellBias; + /// A unique pointer to represent 1D weights tensor with dimensions [num_units]. std::unique_ptr<ScopedCpuTensorHandle> m_OutputGateBias; }; +/// This layer represents a LSTM operation. class LstmLayer : public LayerWithParameters<LstmDescriptor> { public: @@ -53,17 +71,38 @@ public: LstmOptProjectionParameters m_ProjectionParameters; LstmOptPeepholeParameters m_PeepholeParameters; + /// Makes a workload for the LSTM type. + /// @param [in] graph The graph where this layer can be found. + /// @param [in] factory The workload factory which will create the workload. + /// @return A pointer to the created workload, or nullptr if not created. virtual std::unique_ptr<IWorkload> CreateWorkload(const Graph& graph, const IWorkloadFactory& factory) const override; + + /// Creates a dynamically-allocated copy of this layer. + /// @param [in] graph The graph into which this layer is being cloned. LstmLayer* Clone(Graph& graph) const override; + /// Check if the input tensor shape(s) + /// will lead to a valid configuration of @ref LstmLayer. void ValidateTensorShapesFromInputs() override; + + /// By default returns inputShapes if the number of inputs are equal to number of outputs, + /// otherwise infers the output shapes from given input shapes and layer properties. + /// @param [in] inputShapes The input shapes layer has. + /// @return A vector to the inferred output shape. std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override; protected: + /// Constructor to create a LstmLayer. + /// @param [in] param LstmDescriptor to configure the lstm operation. + /// @param [in] name Optional name for the layer. LstmLayer(const LstmDescriptor& param, const char* name); + + /// Default destructor ~LstmLayer() = default; + /// Retrieve the handles to the constant values stored by the layer. + /// @return A vector of the constant tensors stored by this layer. Layer::ConstantTensors GetConstantTensorsByRef() override; }; |