| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #include "QuantizedLstmLayer.hpp" |
| |
| #include "LayerCloneBase.hpp" |
| |
| #include <armnn/TypesUtils.hpp> |
| #include <backendsCommon/CpuTensorHandle.hpp> |
| #include <backendsCommon/WorkloadFactory.hpp> |
| |
| namespace armnn |
| { |
| |
| QuantizedLstmLayer::QuantizedLstmLayer(const char* name) |
| : Layer(3, 2, LayerType::QuantizedLstm, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> QuantizedLstmLayer::CreateWorkload(const Graph& graph, |
| 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(); |
| |
| return factory.CreateQuantizedLstm(descriptor, PrepInfoAndDesc(descriptor, graph)); |
| } |
| |
| QuantizedLstmLayer* QuantizedLstmLayer::Clone(Graph& graph) const |
| { |
| auto layer = CloneBase<QuantizedLstmLayer>(graph, GetName()); |
| |
| layer->m_QuantizedLstmParameters.m_InputToInputWeights = m_QuantizedLstmParameters.m_InputToInputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_InputToInputWeights) : nullptr; |
| layer->m_QuantizedLstmParameters.m_InputToForgetWeights = m_QuantizedLstmParameters.m_InputToForgetWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_InputToForgetWeights) : nullptr; |
| layer->m_QuantizedLstmParameters.m_InputToCellWeights = m_QuantizedLstmParameters.m_InputToCellWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_InputToCellWeights) : nullptr; |
| layer->m_QuantizedLstmParameters.m_InputToOutputWeights = m_QuantizedLstmParameters.m_InputToOutputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_InputToOutputWeights) : nullptr; |
| |
| layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = m_QuantizedLstmParameters.m_RecurrentToInputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_RecurrentToInputWeights) : nullptr; |
| layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = m_QuantizedLstmParameters.m_RecurrentToForgetWeights |
| ? std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_RecurrentToForgetWeights) : nullptr; |
| layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = m_QuantizedLstmParameters.m_RecurrentToCellWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_RecurrentToCellWeights) : nullptr; |
| layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = m_QuantizedLstmParameters.m_RecurrentToOutputWeights |
| ? std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_RecurrentToOutputWeights) : nullptr; |
| |
| layer->m_QuantizedLstmParameters.m_InputGateBias = m_QuantizedLstmParameters.m_InputGateBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_InputGateBias) : nullptr; |
| layer->m_QuantizedLstmParameters.m_ForgetGateBias = m_QuantizedLstmParameters.m_ForgetGateBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_ForgetGateBias) : nullptr; |
| layer->m_QuantizedLstmParameters.m_CellBias = m_QuantizedLstmParameters.m_CellBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_CellBias) : nullptr; |
| layer->m_QuantizedLstmParameters.m_OutputGateBias = m_QuantizedLstmParameters.m_OutputGateBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_QuantizedLstmParameters.m_OutputGateBias) : nullptr; |
| |
| return std::move(layer); |
| } |
| |
| std::vector<TensorShape> QuantizedLstmLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const |
| { |
| BOOST_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()); |
| |
| auto inferredShapes = InferOutputShapes( |
| { |
| GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(), // input |
| GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape(), // previousCellStateIn |
| GetInputSlot(2).GetConnection()->GetTensorInfo().GetShape() // previousOutputIn |
| }); |
| |
| BOOST_ASSERT(inferredShapes.size() == 2); |
| |
| // Check weights and bias for nullptr |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToInputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToInputWeights should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToForgetWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToForgetWeights should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToCellWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToCellWeights should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToOutputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToOutputWeights should not be null."); |
| |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToInputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToInputWeights should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToForgetWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToForgetWeights should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToCellWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToCellWeights should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToOutputWeights != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToOutputWeights should not be null."); |
| |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_InputGateBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputGateBias should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_ForgetGateBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_ForgetGateBias should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_CellBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_CellBias should not be null."); |
| BOOST_ASSERT_MSG(m_QuantizedLstmParameters.m_OutputGateBias != nullptr, |
| "QuantizedLstmLayer: m_QuantizedLstmParameters.m_OutputGateBias should not be null."); |
| |
| // Check output TensorShape(s) match inferred shape |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "QuantizedLstmLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", |
| GetOutputSlot(0).GetTensorInfo().GetShape(), |
| inferredShapes[0]); |
| |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "QuantizedLstmLayer: TensorShape set on OutputSlot[1] does not match the inferred shape.", |
| GetOutputSlot(1).GetTensorInfo().GetShape(), |
| inferredShapes[1]); |
| } |
| |
| Layer::ConstantTensors QuantizedLstmLayer::GetConstantTensorsByRef() |
| { |
| 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::Accept(ILayerVisitor& visitor) const |
| { |
| QuantizedLstmInputParams inputParams; |
| |
| // InputToX weight tensors |
| ConstTensor inputToInputWeightsTensor; |
| if (m_QuantizedLstmParameters.m_InputToInputWeights != nullptr) |
| { |
| ConstTensor inputToInputWeightsTensorCopy(m_QuantizedLstmParameters.m_InputToInputWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_InputToInputWeights->Map(true)); |
| inputToInputWeightsTensor = inputToInputWeightsTensorCopy; |
| inputParams.m_InputToInputWeights = &inputToInputWeightsTensor; |
| } |
| |
| ConstTensor inputToForgetWeightsTensor; |
| if (m_QuantizedLstmParameters.m_InputToForgetWeights != nullptr) |
| { |
| ConstTensor inputToForgetWeightsTensorCopy(m_QuantizedLstmParameters.m_InputToForgetWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_InputToForgetWeights->Map(true)); |
| inputToForgetWeightsTensor = inputToForgetWeightsTensorCopy; |
| inputParams.m_InputToForgetWeights = &inputToForgetWeightsTensor; |
| } |
| |
| ConstTensor inputToCellWeightsTensor; |
| if (m_QuantizedLstmParameters.m_InputToCellWeights != nullptr) |
| { |
| ConstTensor inputToCellWeightsTensorCopy(m_QuantizedLstmParameters.m_InputToCellWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_InputToCellWeights->Map(true)); |
| inputToCellWeightsTensor = inputToCellWeightsTensorCopy; |
| inputParams.m_InputToCellWeights = &inputToCellWeightsTensor; |
| } |
| |
| ConstTensor inputToOutputWeightsTensor; |
| if (m_QuantizedLstmParameters.m_InputToOutputWeights != nullptr) |
| { |
| ConstTensor inputToOutputWeightsTensorCopy(m_QuantizedLstmParameters.m_InputToOutputWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_InputToOutputWeights->Map(true)); |
| inputToOutputWeightsTensor = inputToOutputWeightsTensorCopy; |
| inputParams.m_InputToOutputWeights = &inputToOutputWeightsTensor; |
| } |
| |
| // RecurrentToX weight tensors |
| ConstTensor recurrentToInputWeightsTensor; |
| if (m_QuantizedLstmParameters.m_RecurrentToInputWeights != nullptr) |
| { |
| ConstTensor recurrentToInputWeightsTensorCopy( |
| m_QuantizedLstmParameters.m_RecurrentToInputWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_RecurrentToInputWeights->Map(true)); |
| recurrentToInputWeightsTensor = recurrentToInputWeightsTensorCopy; |
| inputParams.m_RecurrentToInputWeights = &recurrentToInputWeightsTensor; |
| } |
| |
| ConstTensor recurrentToForgetWeightsTensor; |
| if (m_QuantizedLstmParameters.m_RecurrentToForgetWeights != nullptr) |
| { |
| ConstTensor recurrentToForgetWeightsTensorCopy( |
| m_QuantizedLstmParameters.m_RecurrentToForgetWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_RecurrentToForgetWeights->Map(true)); |
| recurrentToForgetWeightsTensor = recurrentToForgetWeightsTensorCopy; |
| inputParams.m_RecurrentToForgetWeights = &recurrentToForgetWeightsTensor; |
| } |
| |
| ConstTensor recurrentToCellWeightsTensor; |
| if (m_QuantizedLstmParameters.m_RecurrentToCellWeights != nullptr) |
| { |
| ConstTensor recurrentToCellWeightsTensorCopy( |
| m_QuantizedLstmParameters.m_RecurrentToCellWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_RecurrentToCellWeights->Map(true)); |
| recurrentToCellWeightsTensor = recurrentToCellWeightsTensorCopy; |
| inputParams.m_RecurrentToCellWeights = &recurrentToCellWeightsTensor; |
| } |
| |
| ConstTensor recurrentToOutputWeightsTensor; |
| if (m_QuantizedLstmParameters.m_RecurrentToOutputWeights != nullptr) |
| { |
| ConstTensor recurrentToOutputWeightsTensorCopy( |
| m_QuantizedLstmParameters.m_RecurrentToOutputWeights->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_RecurrentToOutputWeights->Map(true)); |
| recurrentToOutputWeightsTensor = recurrentToOutputWeightsTensorCopy; |
| inputParams.m_RecurrentToOutputWeights = &recurrentToOutputWeightsTensor; |
| } |
| |
| // Bias tensors |
| ConstTensor inputGateBiasTensor; |
| if (m_QuantizedLstmParameters.m_InputGateBias != nullptr) |
| { |
| ConstTensor inputGateBiasTensorCopy(m_QuantizedLstmParameters.m_InputGateBias->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_InputGateBias->Map(true)); |
| inputGateBiasTensor = inputGateBiasTensorCopy; |
| inputParams.m_InputGateBias = &inputGateBiasTensor; |
| } |
| |
| ConstTensor forgetGateBiasTensor; |
| if (m_QuantizedLstmParameters.m_ForgetGateBias != nullptr) |
| { |
| ConstTensor forgetGateBiasTensorCopy(m_QuantizedLstmParameters.m_ForgetGateBias->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_ForgetGateBias->Map(true)); |
| forgetGateBiasTensor = forgetGateBiasTensorCopy; |
| inputParams.m_ForgetGateBias = &forgetGateBiasTensor; |
| } |
| |
| ConstTensor cellBiasTensor; |
| if (m_QuantizedLstmParameters.m_CellBias != nullptr) |
| { |
| ConstTensor cellBiasTensorCopy(m_QuantizedLstmParameters.m_CellBias->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_CellBias->Map(true)); |
| cellBiasTensor = cellBiasTensorCopy; |
| inputParams.m_CellBias = &cellBiasTensor; |
| } |
| |
| ConstTensor outputGateBiasTensor; |
| if (m_QuantizedLstmParameters.m_OutputGateBias != nullptr) |
| { |
| ConstTensor outputGateBiasCopy(m_QuantizedLstmParameters.m_OutputGateBias->GetTensorInfo(), |
| m_QuantizedLstmParameters.m_OutputGateBias->Map(true)); |
| outputGateBiasTensor = outputGateBiasCopy; |
| inputParams.m_OutputGateBias = &outputGateBiasTensor; |
| } |
| |
| visitor.VisitQuantizedLstmLayer(this, inputParams, GetName()); |
| } |
| |
| } // namespace armnn |
