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//
// 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 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));
}
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
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