| // |
| // Copyright © 2017,2019-2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #include "QuantizedLstmLayer.hpp" |
| |
| #include "LayerCloneBase.hpp" |
| |
| #include <armnn/QuantizedLstmParams.hpp> |
| #include <armnn/TypesUtils.hpp> |
| #include <armnn/backends/TensorHandle.hpp> |
| #include <armnn/backends/WorkloadFactory.hpp> |
| |
| namespace armnn |
| { |
| |
| QuantizedLstmLayer::QuantizedLstmLayer(const char* name) |
| : Layer(3, 2, LayerType::QuantizedLstm, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> QuantizedLstmLayer::CreateWorkload(const IWorkloadFactory& factory) const |
| { |
| QuantizedLstmQueueDescriptor descriptor; |
| |
| // QuantizedLstmLayer parameters - there are no optional params |
| descriptor.m_InputToInputWeights = m_QuantizedLstmParameters.m_InputToInputWeights.get(); |
| descriptor.m_InputToForgetWeights = m_QuantizedLstmParameters.m_InputToForgetWeights.get(); |
| descriptor.m_InputToCellWeights = m_QuantizedLstmParameters.m_InputToCellWeights.get(); |
| descriptor.m_InputToOutputWeights = m_QuantizedLstmParameters.m_InputToOutputWeights.get(); |
| |
| descriptor.m_RecurrentToInputWeights = m_QuantizedLstmParameters.m_RecurrentToInputWeights.get(); |
| descriptor.m_RecurrentToForgetWeights = m_QuantizedLstmParameters.m_RecurrentToForgetWeights.get(); |
| descriptor.m_RecurrentToCellWeights = m_QuantizedLstmParameters.m_RecurrentToCellWeights.get(); |
| descriptor.m_RecurrentToOutputWeights = m_QuantizedLstmParameters.m_RecurrentToOutputWeights.get(); |
| |
| descriptor.m_InputGateBias = m_QuantizedLstmParameters.m_InputGateBias.get(); |
| descriptor.m_ForgetGateBias = m_QuantizedLstmParameters.m_ForgetGateBias.get(); |
| descriptor.m_CellBias = m_QuantizedLstmParameters.m_CellBias.get(); |
| descriptor.m_OutputGateBias = m_QuantizedLstmParameters.m_OutputGateBias.get(); |
| |
| SetAdditionalInfo(descriptor); |
| |
| return factory.CreateWorkload(LayerType::QuantizedLstm, descriptor, PrepInfoAndDesc(descriptor)); |
| } |
| |
| QuantizedLstmLayer* QuantizedLstmLayer::Clone(Graph& graph) const |
| { |
| auto layer = CloneBase<QuantizedLstmLayer>(graph, GetName()); |
| |
| layer->m_QuantizedLstmParameters.m_InputToInputWeights = m_QuantizedLstmParameters.m_InputToInputWeights ? |
| m_QuantizedLstmParameters.m_InputToInputWeights : nullptr; |
| layer->m_QuantizedLstmParameters.m_InputToForgetWeights = m_QuantizedLstmParameters.m_InputToForgetWeights ? |
| m_QuantizedLstmParameters.m_InputToForgetWeights : nullptr; |
| layer->m_QuantizedLstmParameters.m_InputToCellWeights = m_QuantizedLstmParameters.m_InputToCellWeights ? |
| m_QuantizedLstmParameters.m_InputToCellWeights : nullptr; |
| layer->m_QuantizedLstmParameters.m_InputToOutputWeights = m_QuantizedLstmParameters.m_InputToOutputWeights ? |
| m_QuantizedLstmParameters.m_InputToOutputWeights : nullptr; |
| |
| layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = m_QuantizedLstmParameters.m_RecurrentToInputWeights ? |
| m_QuantizedLstmParameters.m_RecurrentToInputWeights : nullptr; |
| layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = m_QuantizedLstmParameters.m_RecurrentToForgetWeights |
| ? m_QuantizedLstmParameters.m_RecurrentToForgetWeights : nullptr; |
| layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = m_QuantizedLstmParameters.m_RecurrentToCellWeights ? |
| m_QuantizedLstmParameters.m_RecurrentToCellWeights : nullptr; |
| layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = m_QuantizedLstmParameters.m_RecurrentToOutputWeights |
| ? m_QuantizedLstmParameters.m_RecurrentToOutputWeights : nullptr; |
| |
| layer->m_QuantizedLstmParameters.m_InputGateBias = m_QuantizedLstmParameters.m_InputGateBias ? |
| m_QuantizedLstmParameters.m_InputGateBias : nullptr; |
| layer->m_QuantizedLstmParameters.m_ForgetGateBias = m_QuantizedLstmParameters.m_ForgetGateBias ? |
| m_QuantizedLstmParameters.m_ForgetGateBias : nullptr; |
| layer->m_QuantizedLstmParameters.m_CellBias = m_QuantizedLstmParameters.m_CellBias ? |
| m_QuantizedLstmParameters.m_CellBias : nullptr; |
| layer->m_QuantizedLstmParameters.m_OutputGateBias = m_QuantizedLstmParameters.m_OutputGateBias ? |
| m_QuantizedLstmParameters.m_OutputGateBias : nullptr; |
| |
| return std::move(layer); |
| } |
| |
| std::vector<TensorShape> QuantizedLstmLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const |
| { |
| ARMNN_ASSERT(inputShapes.size() == 3); |
| |
| // Get input values for validation |
| unsigned int numBatches = inputShapes[0][0]; |
| unsigned int outputSize = inputShapes[1][1]; |
| |
| std::vector<TensorShape> outShapes; |
| outShapes.push_back(TensorShape({numBatches, outputSize})); // cellStateOut |
| outShapes.push_back(TensorShape({numBatches, outputSize})); // output |
| |
| return outShapes; |
| } |
| |
| void QuantizedLstmLayer::ValidateTensorShapesFromInputs() |
| { |
| VerifyLayerConnections(3, CHECK_LOCATION()); |
| |
| const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape(); |
| |
| VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod); |
| |
| auto inferredShapes = InferOutputShapes( |
| { |
| GetInputSlot(0).GetTensorInfo().GetShape(), // input |
| GetInputSlot(1).GetTensorInfo().GetShape(), // previousCellStateIn |
| GetInputSlot(2).GetTensorInfo().GetShape() // previousOutputIn |
| }); |
| |
| ARMNN_ASSERT(inferredShapes.size() == 2); |
| |
| // Check weights and bias for nullptr |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToInputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToInputWeights should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToForgetWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToForgetWeights should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToCellWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToCellWeights should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToOutputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToOutputWeights should not be null."); |
| |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToInputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToInputWeights should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToForgetWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToForgetWeights should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToCellWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToCellWeights should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToOutputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToOutputWeights should not be null."); |
| |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputGateBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputGateBias should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_ForgetGateBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_ForgetGateBias should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_CellBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_CellBias should not be null."); |
| ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_OutputGateBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_OutputGateBias should not be null."); |
| |
| // Check output TensorShape(s) match inferred shape |
| ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "QuantizedLstmLayer"); |
| |
| ValidateAndCopyShape(GetOutputSlot(1).GetTensorInfo().GetShape(), |
| inferredShapes[1], |
| m_ShapeInferenceMethod, |
| "QuantizedLstmLayer", |
| 1); |
| } |
| |
| Layer::ImmutableConstantTensors QuantizedLstmLayer::GetConstantTensorsByRef() const |
| { |
| // For API stability DO NOT ALTER order and add new members to the end of vector |
| return |
| { |
| m_QuantizedLstmParameters.m_InputToInputWeights, |
| m_QuantizedLstmParameters.m_InputToForgetWeights, |
| m_QuantizedLstmParameters.m_InputToCellWeights, |
| m_QuantizedLstmParameters.m_InputToOutputWeights, |
| |
| m_QuantizedLstmParameters.m_RecurrentToInputWeights, |
| m_QuantizedLstmParameters.m_RecurrentToForgetWeights, |
| m_QuantizedLstmParameters.m_RecurrentToCellWeights, |
| m_QuantizedLstmParameters.m_RecurrentToOutputWeights, |
| |
| m_QuantizedLstmParameters.m_InputGateBias, |
| m_QuantizedLstmParameters.m_ForgetGateBias, |
| m_QuantizedLstmParameters.m_CellBias, |
| m_QuantizedLstmParameters.m_OutputGateBias |
| }; |
| } |
| |
| void QuantizedLstmLayer::ExecuteStrategy(IStrategy& strategy) const |
| { |
| std::vector<ConstTensor> constTensors; |
| |
| ManagedConstTensorHandle managedInputToInputWeights(m_QuantizedLstmParameters.m_InputToInputWeights); |
| ManagedConstTensorHandle managedInputToForgetWeights(m_QuantizedLstmParameters.m_InputToForgetWeights); |
| ManagedConstTensorHandle managedInputToCellWeights(m_QuantizedLstmParameters.m_InputToCellWeights); |
| ManagedConstTensorHandle managedInputToOutputWeights(m_QuantizedLstmParameters.m_InputToOutputWeights); |
| |
| ManagedConstTensorHandle managedRecurrentToInputWeights(m_QuantizedLstmParameters.m_RecurrentToInputWeights); |
| ManagedConstTensorHandle managedRecurrentToForgetWeights(m_QuantizedLstmParameters.m_RecurrentToForgetWeights); |
| ManagedConstTensorHandle managedRecurrentToCellWeights(m_QuantizedLstmParameters.m_RecurrentToCellWeights); |
| ManagedConstTensorHandle managedRecurrentToOutputWeights(m_QuantizedLstmParameters.m_RecurrentToOutputWeights); |
| |
| ManagedConstTensorHandle managedInputGateBias(m_QuantizedLstmParameters.m_InputGateBias); |
| ManagedConstTensorHandle managedForgetGateBias(m_QuantizedLstmParameters.m_ForgetGateBias); |
| ManagedConstTensorHandle managedCellBias(m_QuantizedLstmParameters.m_CellBias); |
| ManagedConstTensorHandle managedOutputGateBias(m_QuantizedLstmParameters.m_OutputGateBias); |
| |
| // InputToX weight tensors |
| if (m_QuantizedLstmParameters.m_InputToInputWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(), |
| managedInputToInputWeights.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_InputToForgetWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(), |
| managedInputToForgetWeights.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_InputToCellWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(), |
| managedInputToCellWeights.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_InputToOutputWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(), |
| managedInputToOutputWeights.Map())); |
| } |
| |
| // RecurrentToX weight tensors |
| if (m_QuantizedLstmParameters.m_RecurrentToInputWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor( |
| managedRecurrentToInputWeights.GetTensorInfo(), |
| managedRecurrentToInputWeights.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_RecurrentToForgetWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor( |
| managedRecurrentToForgetWeights.GetTensorInfo(), |
| managedRecurrentToForgetWeights.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_RecurrentToCellWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor( |
| managedRecurrentToCellWeights.GetTensorInfo(), |
| managedRecurrentToCellWeights.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_RecurrentToOutputWeights != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor( |
| managedRecurrentToOutputWeights.GetTensorInfo(), |
| managedRecurrentToOutputWeights.Map())); |
| } |
| |
| // Bias tensors |
| if (m_QuantizedLstmParameters.m_InputGateBias != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedInputGateBias.GetTensorInfo(), |
| managedInputGateBias.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_ForgetGateBias != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedForgetGateBias.GetTensorInfo(), |
| managedForgetGateBias.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_CellBias != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedCellBias.GetTensorInfo(), |
| managedCellBias.Map())); |
| } |
| |
| if (m_QuantizedLstmParameters.m_OutputGateBias != nullptr) |
| { |
| constTensors.emplace_back(ConstTensor(managedOutputGateBias.GetTensorInfo(), |
| managedOutputGateBias.Map())); |
| } |
| |
| |
| strategy.ExecuteStrategy(this, BaseDescriptor(), constTensors, GetName()); |
| } |
| |
| } // namespace armnn |