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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#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
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