James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | #pragma once |
| 6 | |
| 7 | #include <Layer.hpp> |
| 8 | |
| 9 | namespace armnn |
| 10 | { |
| 11 | |
| 12 | class ScopedCpuTensorHandle; |
| 13 | |
| 14 | struct QuantizedLstmParameters |
| 15 | { |
| 16 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8). |
| 17 | std::unique_ptr<ScopedCpuTensorHandle> m_InputToInputWeights; |
| 18 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8). |
| 19 | std::unique_ptr<ScopedCpuTensorHandle> m_InputToForgetWeights; |
| 20 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8). |
| 21 | std::unique_ptr<ScopedCpuTensorHandle> m_InputToCellWeights; |
| 22 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8). |
| 23 | std::unique_ptr<ScopedCpuTensorHandle> m_InputToOutputWeights; |
| 24 | |
| 25 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8). |
| 26 | std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToInputWeights; |
| 27 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8). |
| 28 | std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToForgetWeights; |
| 29 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8). |
| 30 | std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToCellWeights; |
| 31 | /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8). |
| 32 | std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToOutputWeights; |
| 33 | |
| 34 | /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). |
| 35 | std::unique_ptr<ScopedCpuTensorHandle> m_InputGateBias; |
| 36 | /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). |
| 37 | std::unique_ptr<ScopedCpuTensorHandle> m_ForgetGateBias; |
| 38 | /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). |
| 39 | std::unique_ptr<ScopedCpuTensorHandle> m_CellBias; |
| 40 | /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). |
| 41 | std::unique_ptr<ScopedCpuTensorHandle> m_OutputGateBias; |
| 42 | }; |
| 43 | |
| 44 | /// This layer represents a QuantizedLstm operation. |
| 45 | class QuantizedLstmLayer : public Layer |
| 46 | { |
| 47 | public: |
| 48 | |
| 49 | QuantizedLstmParameters m_QuantizedLstmParameters; |
| 50 | |
| 51 | /// Makes a workload for the QuantizedLstm type. |
| 52 | /// @param [in] graph The graph where this layer can be found. |
| 53 | /// @param [in] factory The workload factory which will create the workload. |
| 54 | /// @return A pointer to the created workload, or nullptr if not created. |
Derek Lamberti | 94a88d2 | 2019-12-10 21:12:59 +0000 | [diff] [blame] | 55 | virtual std::unique_ptr<IWorkload> CreateWorkload(const IWorkloadFactory& factory) const override; |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 56 | |
| 57 | /// Creates a dynamically-allocated copy of this layer. |
| 58 | /// @param [in] graph The graph into which this layer is being cloned. |
| 59 | QuantizedLstmLayer* Clone(Graph& graph) const override; |
| 60 | |
| 61 | /// Check if the input tensor shape(s) |
| 62 | /// will lead to a valid configuration of @ref QuantizedLstmLayer. |
Teresa Charlin | cdc0149 | 2020-06-09 18:00:20 +0100 | [diff] [blame^] | 63 | /// @param [in] shapeInferenceMethod Indicates if output shape shall be overwritten or just validated. |
| 64 | void ValidateTensorShapesFromInputs( |
| 65 | ShapeInferenceMethod shapeInferenceMethod = ShapeInferenceMethod::ValidateOnly) override; |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 66 | |
| 67 | /// By default returns inputShapes if the number of inputs are equal to number of outputs, |
| 68 | /// otherwise infers the output shapes from given input shapes and layer properties. |
| 69 | /// @param [in] inputShapes The input shapes layer has. |
| 70 | /// @return A vector to the inferred output shape. |
| 71 | std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override; |
| 72 | |
| 73 | void Accept(ILayerVisitor& visitor) const override; |
| 74 | |
| 75 | protected: |
| 76 | /// Constructor to create a QuantizedLstmLayer. |
| 77 | /// @param [in] name Optional name for the layer. |
| 78 | QuantizedLstmLayer(const char* name); |
| 79 | |
| 80 | /// Default destructor |
| 81 | ~QuantizedLstmLayer() = default; |
| 82 | |
| 83 | /// Retrieve the handles to the constant values stored by the layer. |
| 84 | /// @return A vector of the constant tensors stored by this layer. |
| 85 | Layer::ConstantTensors GetConstantTensorsByRef() override; |
| 86 | }; |
| 87 | |
| 88 | } // namespace armnn |