#include <FullyConnectedLayer.h>

Collaboration diagram for onert::backend::train::ops::FullyConnectedLayer:

[legend]

Public Member Functions
	FullyConnectedLayer ()

	~FullyConnectedLayer ()

void	configureBackward (const IPortableTensor input, const IPortableTensor weights, IPortableTensor output, IPortableTensor back_prop_input, IPortableTensor grad_weights, IPortableTensor grad_bias, const IPortableTensor *back_prop_output, ir::Activation activation, ir::FullyConnectedWeightsFormat weights_format)

void	forward (bool training) override

void	backward () override

Public Member Functions inherited from onert::exec::train::ITrainableFunction
virtual	~ITrainableFunction ()=default

virtual std::optional< backend::train::LayerScopeTensors >	registerLayerScopeTensors ()

Public Member Functions inherited from onert::backend::cpu::ops::FullyConnectedLayer
	FullyConnectedLayer ()

	~FullyConnectedLayer ()

void	fullyConnectedFloat32 ()

void	fullyConnectedQuant8 ()

void	fullyConnectedHybrid ()

void	fullyConnectedSparseWeight ()

void	fullyConnectedGGMLWeight ()

void	fullyConnected16x1Float32 ()

void	configure (const IPortableTensor input, const IPortableTensor weights, const IPortableTensor bias, ir::Activation activation, ir::FullyConnectedWeightsFormat weights_format, IPortableTensor output, const std::shared_ptr< ExternalContext > &external_context)

void	run () override

void	prepare () override

Public Member Functions inherited from onert::exec::IFunction
virtual	~IFunction ()=default

Additional Inherited Members
Protected Attributes inherited from onert::backend::cpu::ops::FullyConnectedLayer
const IPortableTensor *	_input

const IPortableTensor *	_weights

const IPortableTensor *	_bias

IPortableTensor *	_output

ir::Activation	_activation

std::unique_ptr< nnfw::cker::FCTempArena >	_temp_arena

std::shared_ptr< ExternalContext >	_external_context

bool	_is_hybrid: 1

bool	_is_shuffled16x1float32: 1

Detailed Description

Definition at line 29 of file FullyConnectedLayer.h.

Constructor & Destructor Documentation

◆ FullyConnectedLayer()

onert::backend::train::ops::FullyConnectedLayer::FullyConnectedLayer ( )

Definition at line 49 of file FullyConnectedLayer.cc.

  : cpu::ops::FullyConnectedLayer{}, _grad_weights{nullptr}, _grad_bias{nullptr},
    _back_prop_input{nullptr}, _back_prop_output{nullptr}, _transposed_weights{nullptr},
    _transposed_input{nullptr}, _transposed_back_prop_output{nullptr},
    _act_back_prop_output{nullptr}
{
  // DO NOTHING
}

◆ ~FullyConnectedLayer()

onert::backend::train::ops::FullyConnectedLayer::~FullyConnectedLayer ( )

default

Member Function Documentation

◆ backward()

void onert::backend::train::ops::FullyConnectedLayer::backward ( )

overridevirtual

Implements onert::exec::train::ITrainableFunction.

Definition at line 102 of file FullyConnectedLayer.cc.

{
  const auto data_type = _back_prop_output->data_type();
  assert(data_type == _input->data_type());
  switch (data_type)
  {
    case OperandType::FLOAT32:
    {
      assert(data_type == _grad_weights->data_type());
      assert(_grad_bias == nullptr || data_type == _grad_bias->data_type());
      backwardFloat32();
      break;
    }
    default:
      throw std::runtime_error{"train FullyConnectedLayer: unsupported data type"};
  }
}

References onert::backend::cpu::ops::FullyConnectedLayer::_input, and onert::backend::IPortableTensor::data_type().

◆ configureBackward()

void onert::backend::train::ops::FullyConnectedLayer::configureBackward	(	const IPortableTensor *	input,
		const IPortableTensor *	weights,
		IPortableTensor *	output,
		IPortableTensor *	back_prop_input,
		IPortableTensor *	grad_weights,
		IPortableTensor *	grad_bias,
		const IPortableTensor *	back_prop_output,
		ir::Activation	activation,
		ir::FullyConnectedWeightsFormat	weights_format
	)

Definition at line 60 of file FullyConnectedLayer.cc.

{
  _back_prop_input = back_prop_input;
  _grad_weights = grad_weights;
  _grad_bias = grad_bias;
  _back_prop_output = back_prop_output;
 
  if (weights_format != ir::FullyConnectedWeightsFormat::Default)
    throw std::runtime_error{
      "train FullyConnectedLayer: Weight formats other than default are not supported."};
 
  if (input->get_info().shape().rank() != 2 || weights->get_info().shape().rank() != 2 ||
      output->get_info().shape().rank() != 2 || back_prop_input->get_info().shape().rank() != 2 ||
      grad_weights->get_info().shape().rank() != 2 ||
      back_prop_output->get_info().shape().rank() != 2)
    throw std::runtime_error{
      "train FullyConnectedLayer: Input other ranks than 2 are not supported."};
 
  _transposed_weights = createTransposedTensor(weights);
  _transposed_weights->setBuffer(std::make_shared<basic::Allocator>(weights->total_size()));
 
  _transposed_input = createTransposedTensor(input);
  _transposed_input->setBuffer(std::make_shared<basic::Allocator>(input->total_size()));
 
  _transposed_back_prop_output = createTransposedTensor(back_prop_output);
  _transposed_back_prop_output->setBuffer(
    std::make_shared<basic::Allocator>(back_prop_output->total_size()));
 
  if (activation != ir::Activation::NONE)
  {
    _act_back_prop_output = std::make_unique<Tensor>(_back_prop_output->get_info());
    _act_back_prop_output->setBuffer(
      std::make_shared<basic::Allocator>(_back_prop_output->total_size()));
  }
}