| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // See LICENSE file in the project root for full license information. |
| // |
| #include "LstmLayer.hpp" |
| |
| #include "LayerCloneBase.hpp" |
| |
| #include <armnn/TypesUtils.hpp> |
| #include <backends/CpuTensorHandle.hpp> |
| #include <backends/WorkloadFactory.hpp> |
| |
| namespace armnn |
| { |
| |
| LstmLayer::LstmLayer(const LstmDescriptor& param, const char* name) |
| : LayerWithParameters(3, 4, LayerType::Lstm, param, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> LstmLayer::CreateWorkload(const Graph& graph, const IWorkloadFactory& factory) const |
| { |
| LstmQueueDescriptor descriptor; |
| |
| // Basic parameters |
| descriptor.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights.get(); |
| descriptor.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights.get(); |
| descriptor.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights.get(); |
| descriptor.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights.get(); |
| descriptor.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights.get(); |
| descriptor.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights.get(); |
| descriptor.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias.get(); |
| descriptor.m_CellBias = m_BasicParameters.m_CellBias.get(); |
| descriptor.m_OutputGateBias = m_BasicParameters.m_OutputGateBias.get(); |
| |
| // Cifg parameters |
| if (!m_Param.m_CifgEnabled) |
| { |
| descriptor.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights.get(); |
| descriptor.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights.get(); |
| descriptor.m_CellToInputWeights = m_CifgParameters.m_CellToInputWeights.get(); |
| descriptor.m_InputGateBias = m_CifgParameters.m_InputGateBias.get(); |
| } |
| |
| // Projection parameters |
| if (m_Param.m_ProjectionEnabled) |
| { |
| descriptor.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights.get(); |
| descriptor.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias.get(); |
| } |
| |
| // Peephole parameters |
| if (m_Param.m_PeepholeEnabled) |
| { |
| descriptor.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights.get(); |
| descriptor.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights.get(); |
| } |
| return factory.CreateLstm(descriptor, PrepInfoAndDesc(descriptor, graph)); |
| } |
| |
| LstmLayer* LstmLayer::Clone(Graph& graph) const |
| { |
| auto layer = CloneBase<LstmLayer>(graph, m_Param, GetName()); |
| |
| layer->m_BasicParameters.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_InputToForgetWeights) |
| : nullptr; |
| layer->m_BasicParameters.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_InputToCellWeights) : nullptr; |
| layer->m_BasicParameters.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_InputToOutputWeights) : nullptr; |
| layer->m_BasicParameters.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_RecurrentToForgetWeights) : nullptr; |
| layer->m_BasicParameters.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_RecurrentToCellWeights) : nullptr; |
| layer->m_BasicParameters.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_RecurrentToOutputWeights) : nullptr; |
| layer->m_BasicParameters.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_ForgetGateBias) : nullptr; |
| layer->m_BasicParameters.m_CellBias = m_BasicParameters.m_CellBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_CellBias) : nullptr; |
| layer->m_BasicParameters.m_OutputGateBias = m_BasicParameters.m_OutputGateBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_OutputGateBias) : nullptr; |
| |
| if (!m_Param.m_CifgEnabled) |
| { |
| layer->m_CifgParameters.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_InputToInputWeights) : nullptr; |
| layer->m_CifgParameters.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_RecurrentToInputWeights) : nullptr; |
| layer->m_CifgParameters.m_CellToInputWeights = m_CifgParameters.m_CellToInputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_CellToInputWeights) : nullptr; |
| layer->m_CifgParameters.m_InputGateBias = m_CifgParameters.m_InputGateBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_InputGateBias) : nullptr; |
| } |
| |
| if (m_Param.m_ProjectionEnabled) |
| { |
| layer->m_ProjectionParameters.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_ProjectionParameters.m_ProjectionWeights) : nullptr; |
| layer->m_ProjectionParameters.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_ProjectionParameters.m_ProjectionBias) : nullptr; |
| } |
| |
| if (m_Param.m_PeepholeEnabled) |
| { |
| layer->m_PeepholeParameters.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_PeepholeParameters.m_CellToForgetWeights) : nullptr; |
| layer->m_PeepholeParameters.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights ? |
| std::make_unique<ScopedCpuTensorHandle>(*m_PeepholeParameters.m_CellToOutputWeights) : nullptr; |
| } |
| |
| return std::move(layer); |
| } |
| |
| std::vector<TensorShape> LstmLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const |
| { |
| BOOST_ASSERT(inputShapes.size() == 3); |
| |
| // Get input values for validation |
| unsigned int batchSize = inputShapes[0][0]; |
| unsigned int outputSize = inputShapes[1][1]; |
| unsigned int numUnits = inputShapes[2][1]; |
| |
| std::vector<TensorShape> outShapes; |
| if (!m_Param.m_CifgEnabled) |
| { |
| outShapes.push_back(TensorShape({batchSize, numUnits*3})); |
| } |
| else |
| { |
| outShapes.push_back(TensorShape({batchSize, numUnits*4})); |
| } |
| outShapes.push_back(TensorShape({batchSize, outputSize})); |
| outShapes.push_back(TensorShape({batchSize, numUnits})); |
| outShapes.push_back(TensorShape({batchSize, outputSize})); |
| |
| return outShapes; |
| } |
| |
| void LstmLayer::ValidateTensorShapesFromInputs() |
| { |
| VerifyLayerConnections(3, CHECK_LOCATION()); |
| |
| auto inferredShapes = InferOutputShapes( { |
| GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(), |
| GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape(), |
| GetInputSlot(2).GetConnection()->GetTensorInfo().GetShape()} |
| ); |
| |
| BOOST_ASSERT(inferredShapes.size() == 4); |
| |
| // Check if the weights are nullptr |
| BOOST_ASSERT_MSG(m_BasicParameters.m_InputToForgetWeights != nullptr, |
| "LstmLayer: m_BasicParameters.m_InputToForgetWeights should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_InputToCellWeights != nullptr, |
| "LstmLayer: m_BasicParameters.m_InputToCellWeights should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_InputToOutputWeights != nullptr, |
| "LstmLayer: m_BasicParameters.m_InputToOutputWeights should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_RecurrentToForgetWeights != nullptr, |
| "LstmLayer: m_BasicParameters.m_RecurrentToForgetWeights should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_RecurrentToCellWeights != nullptr, |
| "LstmLayer: m_BasicParameters.m_RecurrentToCellWeights should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_RecurrentToOutputWeights != nullptr, |
| "LstmLayer: m_BasicParameters.m_RecurrentToOutputWeights should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_ForgetGateBias != nullptr, |
| "LstmLayer: m_BasicParameters.m_ForgetGateBias should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_CellBias != nullptr, |
| "LstmLayer: m_BasicParameters.m_CellBias should not be null."); |
| BOOST_ASSERT_MSG(m_BasicParameters.m_OutputGateBias != nullptr, |
| "LstmLayer: m_BasicParameters.m_OutputGateBias should not be null."); |
| |
| if (!m_Param.m_CifgEnabled) |
| { |
| BOOST_ASSERT_MSG(m_CifgParameters.m_InputToInputWeights != nullptr, |
| "LstmLayer: m_CifgParameters.m_InputToInputWeights should not be null."); |
| BOOST_ASSERT_MSG(m_CifgParameters.m_RecurrentToInputWeights != nullptr, |
| "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not be null."); |
| BOOST_ASSERT_MSG(m_CifgParameters.m_InputGateBias != nullptr, |
| "LstmLayer: m_CifgParameters.m_InputGateBias should not be null."); |
| |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "LstmLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", |
| GetOutputSlot(0).GetTensorInfo().GetShape(), |
| inferredShapes[0]); |
| } |
| else |
| { |
| BOOST_ASSERT_MSG(m_CifgParameters.m_InputToInputWeights == nullptr, |
| "LstmLayer: m_CifgParameters.m_InputToInputWeights should not have a value when CIFG is enabled."); |
| BOOST_ASSERT_MSG(m_CifgParameters.m_RecurrentToInputWeights == nullptr, |
| "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not have a value when CIFG is enabled."); |
| BOOST_ASSERT_MSG(m_CifgParameters.m_CellToInputWeights == nullptr, |
| "LstmLayer: m_CifgParameters.m_CellToInputWeights should not have a value when CIFG is enabled."); |
| BOOST_ASSERT_MSG(m_CifgParameters.m_InputGateBias == nullptr, |
| "LstmLayer: m_CifgParameters.m_InputGateBias should not have a value when CIFG is enabled."); |
| |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "LstmLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", |
| GetOutputSlot(0).GetTensorInfo().GetShape(), |
| inferredShapes[0]); |
| } |
| |
| if (m_Param.m_ProjectionEnabled) |
| { |
| BOOST_ASSERT_MSG(m_ProjectionParameters.m_ProjectionWeights != nullptr, |
| "LstmLayer: m_ProjectionParameters.m_ProjectionWeights should not be null."); |
| } |
| |
| if (m_Param.m_PeepholeEnabled) |
| { |
| BOOST_ASSERT_MSG(m_PeepholeParameters.m_CellToForgetWeights != nullptr, |
| "LstmLayer: m_PeepholeParameters.m_CellToForgetWeights should not be null."); |
| BOOST_ASSERT_MSG(m_PeepholeParameters.m_CellToOutputWeights != nullptr, |
| "LstmLayer: m_PeepholeParameters.m_CellToOutputWeights should not be null."); |
| } |
| |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "LstmLayer: TensorShape set on OutputSlot[1] does not match the inferred shape.", |
| GetOutputSlot(1).GetTensorInfo().GetShape(), |
| inferredShapes[1]); |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "LstmLayer: TensorShape set on OutputSlot[2] does not match the inferred shape.", |
| GetOutputSlot(2).GetTensorInfo().GetShape(), |
| inferredShapes[2]); |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "LstmLayer: TensorShape set on OutputSlot[3] does not match the inferred shape.", |
| GetOutputSlot(3).GetTensorInfo().GetShape(), |
| inferredShapes[3]); |
| } |
| |
| Layer::ConstantTensors LstmLayer::GetConstantTensorsByRef() |
| { |
| return {m_BasicParameters.m_InputToForgetWeights, |
| m_BasicParameters.m_InputToCellWeights, |
| m_BasicParameters.m_InputToOutputWeights, |
| m_BasicParameters.m_RecurrentToForgetWeights, |
| m_BasicParameters.m_RecurrentToCellWeights, |
| m_BasicParameters.m_RecurrentToOutputWeights, |
| m_BasicParameters.m_ForgetGateBias, |
| m_BasicParameters.m_CellBias, |
| m_BasicParameters.m_OutputGateBias, |
| |
| // Cifg parameters |
| m_CifgParameters.m_InputToInputWeights, |
| m_CifgParameters.m_RecurrentToInputWeights, |
| m_CifgParameters.m_CellToInputWeights, |
| m_CifgParameters.m_InputGateBias, |
| |
| // Projection parameters |
| m_ProjectionParameters.m_ProjectionWeights, |
| m_ProjectionParameters.m_ProjectionBias, |
| |
| // Peephole parameters |
| m_PeepholeParameters.m_CellToForgetWeights, |
| m_PeepholeParameters.m_CellToOutputWeights}; |
| } |
| |
| } // namespace armnn |