// // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #include "QuantizedLstmLayer.hpp" #include "LayerCloneBase.hpp" #include #include #include #include namespace armnn { QuantizedLstmLayer::QuantizedLstmLayer(const char* name) : Layer(3, 2, LayerType::QuantizedLstm, name) { } std::unique_ptr 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(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 QuantizedLstmLayer::InferOutputShapes(const std::vector& 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 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).GetConnection()->GetTensorInfo().GetShape(), // input GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape(), // previousCellStateIn GetInputSlot(2).GetConnection()->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::ConstantTensors QuantizedLstmLayer::GetConstantTensorsByRef() { // 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 }; } ARMNN_NO_DEPRECATE_WARN_BEGIN void QuantizedLstmLayer::Accept(ILayerVisitor& visitor) const { QuantizedLstmInputParams inputParams; 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 ConstTensor inputToInputWeightsTensor; if (m_QuantizedLstmParameters.m_InputToInputWeights != nullptr) { ConstTensor inputToInputWeightsTensorCopy(managedInputToInputWeights.GetTensorInfo(), managedInputToInputWeights.Map()); inputToInputWeightsTensor = inputToInputWeightsTensorCopy; inputParams.m_InputToInputWeights = &inputToInputWeightsTensor; } ConstTensor inputToForgetWeightsTensor; if (m_QuantizedLstmParameters.m_InputToForgetWeights != nullptr) { ConstTensor inputToForgetWeightsTensorCopy(managedInputToForgetWeights.GetTensorInfo(), managedInputToForgetWeights.Map()); inputToForgetWeightsTensor = inputToForgetWeightsTensorCopy; inputParams.m_InputToForgetWeights = &inputToForgetWeightsTensor; } ConstTensor inputToCellWeightsTensor; if (m_QuantizedLstmParameters.m_InputToCellWeights != nullptr) { ConstTensor inputToCellWeightsTensorCopy(managedInputToCellWeights.GetTensorInfo(), managedInputToCellWeights.Map()); inputToCellWeightsTensor = inputToCellWeightsTensorCopy; inputParams.m_InputToCellWeights = &inputToCellWeightsTensor; } ConstTensor inputToOutputWeightsTensor; if (m_QuantizedLstmParameters.m_InputToOutputWeights != nullptr) { ConstTensor inputToOutputWeightsTensorCopy(managedInputToOutputWeights.GetTensorInfo(), managedInputToOutputWeights.Map()); inputToOutputWeightsTensor = inputToOutputWeightsTensorCopy; inputParams.m_InputToOutputWeights = &inputToOutputWeightsTensor; } // RecurrentToX weight tensors ConstTensor recurrentToInputWeightsTensor; if (m_QuantizedLstmParameters.m_RecurrentToInputWeights != nullptr) { ConstTensor recurrentToInputWeightsTensorCopy( managedRecurrentToInputWeights.GetTensorInfo(), managedRecurrentToInputWeights.Map()); recurrentToInputWeightsTensor = recurrentToInputWeightsTensorCopy; inputParams.m_RecurrentToInputWeights = &recurrentToInputWeightsTensor; } ConstTensor recurrentToForgetWeightsTensor; if (m_QuantizedLstmParameters.m_RecurrentToForgetWeights != nullptr) { ConstTensor recurrentToForgetWeightsTensorCopy( managedRecurrentToForgetWeights.GetTensorInfo(), managedRecurrentToForgetWeights.Map()); recurrentToForgetWeightsTensor = recurrentToForgetWeightsTensorCopy; inputParams.m_RecurrentToForgetWeights = &recurrentToForgetWeightsTensor; } ConstTensor recurrentToCellWeightsTensor; if (m_QuantizedLstmParameters.m_RecurrentToCellWeights != nullptr) { ConstTensor recurrentToCellWeightsTensorCopy( managedRecurrentToCellWeights.GetTensorInfo(), managedRecurrentToCellWeights.Map()); recurrentToCellWeightsTensor = recurrentToCellWeightsTensorCopy; inputParams.m_RecurrentToCellWeights = &recurrentToCellWeightsTensor; } ConstTensor recurrentToOutputWeightsTensor; if (m_QuantizedLstmParameters.m_RecurrentToOutputWeights != nullptr) { ConstTensor recurrentToOutputWeightsTensorCopy( managedRecurrentToOutputWeights.GetTensorInfo(), managedRecurrentToOutputWeights.Map()); recurrentToOutputWeightsTensor = recurrentToOutputWeightsTensorCopy; inputParams.m_RecurrentToOutputWeights = &recurrentToOutputWeightsTensor; } // Bias tensors ConstTensor inputGateBiasTensor; if (m_QuantizedLstmParameters.m_InputGateBias != nullptr) { ConstTensor inputGateBiasTensorCopy(managedInputGateBias.GetTensorInfo(), managedInputGateBias.Map()); inputGateBiasTensor = inputGateBiasTensorCopy; inputParams.m_InputGateBias = &inputGateBiasTensor; } ConstTensor forgetGateBiasTensor; if (m_QuantizedLstmParameters.m_ForgetGateBias != nullptr) { ConstTensor forgetGateBiasTensorCopy(managedForgetGateBias.GetTensorInfo(), managedForgetGateBias.Map()); forgetGateBiasTensor = forgetGateBiasTensorCopy; inputParams.m_ForgetGateBias = &forgetGateBiasTensor; } ConstTensor cellBiasTensor; if (m_QuantizedLstmParameters.m_CellBias != nullptr) { ConstTensor cellBiasTensorCopy(managedCellBias.GetTensorInfo(), managedCellBias.Map()); cellBiasTensor = cellBiasTensorCopy; inputParams.m_CellBias = &cellBiasTensor; } ConstTensor outputGateBiasTensor; if (m_QuantizedLstmParameters.m_OutputGateBias != nullptr) { ConstTensor outputGateBiasCopy(managedOutputGateBias.GetTensorInfo(), managedOutputGateBias.Map()); outputGateBiasTensor = outputGateBiasCopy; inputParams.m_OutputGateBias = &outputGateBiasTensor; } visitor.VisitQuantizedLstmLayer(this, inputParams, GetName()); } ARMNN_NO_DEPRECATE_WARN_END void QuantizedLstmLayer::ExecuteStrategy(IStrategy& strategy) const { std::vector 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