#include </home/runner/work/lima/lima/deeplima/libs/tasks/graph_dp/model/birnn_and_deep_biaffine_attention.h>

Inheritance diagram for deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl:

Public Types
typedef torch::Tensor	tensor_t

typedef DictsHolder	dicts_holder_t

Public Member Functions
	BiRnnAndDeepBiaffineAttentionImpl ()

	BiRnnAndDeepBiaffineAttentionImpl (DictsHolder &&dicts, const std::vector< nets::embd_descr_t > &embd_descr, const std::vector< nets::rnn_descr_t > &rnn_descr, const std::vector< nets::deep_biaffine_attention_descr_t > &decoder_descr, const std::vector< std::string > &output_names, DictsHolder &&classes, const std::string &embd_fn, bool input_includes_root, int64_t num_labels=0, const std::vector< std::string > &rel_class_names={})

virtual void	load (torch::serialize::InputArchive &archive)

virtual void	save (torch::serialize::OutputArchive &archive) const

void	load (const std::string &fn)

size_t	init_new_worker (size_t)

void	train (const train_params_graph_dp_t &params, const std::vector< std::string > &output_names, const IterableDataSet &train_batches, const IterableDataSet &eval_batches, torch::optim::Optimizer &opt, double &best_eval_accuracy, const torch::Device &device=torch::Device(torch::kCPU))

void	evaluate (const std::vector< std::string > &output_names, std::shared_ptr< BatchIterator > dataset_iterator, nets::epoch_stat_t &stat, const torch::Device &device=torch::Device(torch::kCPU))

void	predict (size_t worker_id, const torch::Tensor &inputs, int64_t input_begin, int64_t input_end, int64_t output_begin, int64_t output_end, std::shared_ptr< StdMatrix< uint8_t > > &output, const std::vector< std::string > &outputs_names, const torch::Device &device=torch::Device(torch::kCPU))

const DictsHolder &	get_classes () const

const std::vector< std::string > &	get_output_class_names () const

const std::vector< std::string > &	get_input_class_names () const

const std::vector< std::string > &	get_rel_class_names () const

const std::string &	get_embd_fn (size_t idx) const

Public Member Functions inherited from deeplima::nets::BiRnnClassifierImpl
	BiRnnClassifierImpl ()

	BiRnnClassifierImpl (DictsHolder &&dicts, const std::vector< embd_descr_t > &embd_descr, const std::vector< rnn_descr_t > &rnn_descr, const std::vector< std::string > &output_names, const std::vector< uint32_t > &classes, float input_dropout_prob)

	BiRnnClassifierImpl (DictsHolder &&dicts, const std::vector< embd_descr_t > &embd_descr, const std::string &script)

const std::vector< embd_descr_t > &	get_embd_descr () const

void	train (size_t epochs, size_t batch_size, size_t seq_len, const std::vector< std::string > &output_names, const TorchMatrix< int64_t > &train_input, const TorchMatrix< int64_t > &train_gold, const TorchMatrix< int64_t > &eval_input, const TorchMatrix< int64_t > &eval_gold, torch::optim::Optimizer &opt, const std::string &model_name="", const torch::Device &device=torch::Device(torch::kCPU))

void	evaluate (const std::vector< std::string > &output_name, const TorchMatrix< int64_t > &input, const TorchMatrix< int64_t > &gold, epoch_stat_t &stat, const torch::Device &device=torch::Device(torch::kCPU))

torch::Tensor	predict (const std::string &output_name, const torch::Tensor &input, const torch::Device &device=torch::Device(torch::kCPU))

torch::Tensor	predict (const std::vector< std::string > &output_names, const torch::Tensor &input, const torch::Device &device=torch::Device(torch::kCPU))

void	predict (size_t worker_id, const torch::Tensor &inputs, int64_t input_begin, int64_t input_end, int64_t output_begin, int64_t output_end, std::shared_ptr< StdMatrix< uint8_t > > &output, const std::vector< std::string > &outputs_names, const torch::Device &device=torch::Device(torch::kCPU))

Public Member Functions inherited from deeplima::nets::StaticGraphImpl
	StaticGraphImpl (const DictsHolder &dicts, const std::string &script)

	StaticGraphImpl (DictsHolder &&dicts, const std::string &script)

	StaticGraphImpl ()

virtual void	set_tags (const std::map< std::string, std::string > &tags)

virtual const std::map< std::string, std::string > &	get_tags () const

virtual bool	has_tag (const std::string &key) const

virtual void	to (torch::Device device, bool non_blocking=false) override

std::map< std::string, torch::Tensor >	forward (const std::map< std::string, torch::Tensor > &inputs, const std::string &output_name)

std::map< std::string, torch::Tensor >	forward (const std::map< std::string, torch::Tensor > &inputs, const std::vector< std::string > &output_names)

template<class InputIt >
std::map< std::string, torch::Tensor >	forward (const std::map< std::string, torch::Tensor > &inputs, InputIt outputs_begin, InputIt outputs_end)

virtual void	pretty_dump (std::ostream &stream) const

const DictsHolder &	get_dicts () const

const std::string &	get_script () const

const std::vector< torch::nn::LSTM > &	get_layers_lstm () const

const std::vector< torch::nn::Linear > &	get_layers_linear () const

const std::vector< torch::nn::Embedding > &	get_layers_embedding () const

const std::vector< torch::nn::Dropout > &	get_layers_dropout () const

const std::vector< deeplima::nets::torch_modules::DeepBiaffineAttentionDecoder > &	get_layers_deep_biaffine_attn_decoder () const

const std::vector< deeplima::nets::torch_modules::DeepBiaffineAttentionLabelDecoder > &	get_layers_deep_biaffine_attn_label_decoder () const

torch::nn::Embedding	get_module_by_name (const std::string &name) const

const std::string	get_module_name (size_t idx, const std::string &type) const

Protected Member Functions
void	train_epoch (size_t batch_size, size_t seq_len, const std::vector< std::string > &output_names, std::shared_ptr< BatchIterator > train_iterator, torch::optim::Optimizer &opt, nets::epoch_stat_t &stat, const torch::Device &device)

void	train_batch (size_t batch_size, size_t seq_len, const std::vector< std::string > &output_names, const torch::Tensor &trainable_input, const torch::Tensor &nontrainable_input, const torch::Tensor &gold, torch::optim::Optimizer &opt, nets::epoch_stat_t &stat, const torch::Device &device)

void	evaluate (const std::vector< std::string > &output_names, const torch::Tensor &trainable_input, const torch::Tensor &nontrainable_input, const torch::Tensor &gold, nets::epoch_stat_t &stat, const torch::Device &device)

Protected Member Functions inherited from deeplima::nets::BiRnnClassifierImpl
void	split_input (const torch::Tensor &src, std::map< std::string, torch::Tensor > &dst, const torch::Device &device)

void	evaluate (const std::vector< std::string > &output_names, const std::map< std::string, torch::Tensor > &input, const torch::Tensor &target, epoch_stat_t &stat, const torch::Device &device)

void	train_epoch (size_t batch_size, size_t seq_len, const std::vector< std::string > &output_names, const torch::Tensor &input_batches, const torch::Tensor &gold_batches, torch::optim::Optimizer &opt, epoch_stat_t &stat, const torch::Device &device)

void	train_batch (size_t batch_size, size_t seq_len, const std::vector< std::string > &output_names, const torch::Tensor &input, const torch::Tensor &gold, torch::optim::Optimizer &opt, epoch_stat_t &stat, const torch::Device &device)

void	train_batch (size_t batch_size, size_t seq_len, const std::vector< std::string > &output_names, const std::map< std::string, torch::Tensor > &input, const torch::Tensor &target, torch::optim::Optimizer &opt, epoch_stat_t &stat, const torch::Device &device)

Protected Member Functions inherited from deeplima::nets::StaticGraphImpl
virtual void	parse_script (const std::string &script)

virtual step_descr_t	parse_script_line (const std::string &line)

virtual std::map< std::string, std::string >	parse_options (std::istringstream &ss)

virtual std::vector< std::string >	parse_list (std::string &str, char sep)

virtual std::vector< int64_t >	parse_iargs (const std::string &str)

template<class InputIt >
void	prepare_exec_plan (const std::map< std::string, torch::Tensor > &inputs, InputIt outputs_begin, InputIt outputs_end)

template<class InputIt >
std::string	get_exec_plan_key (const std::map< std::string, torch::Tensor > &inputs, InputIt outputs_begin, InputIt outputs_end)

template<class T >
T	get_option (const std::map< std::string, std::string > &opts, const std::string &name)

bool	get_bool_option (const std::map< std::string, std::string > &opts, const std::string &name)

virtual void	create_arg (const std::vector< std::string > &names, const std::map< std::string, std::string > &opts)

virtual void	create_submodule_Embedding (const std::string &name, const std::map< std::string, std::string > &opts)

virtual void	create_submodule_LSTM (const std::string &name, const std::map< std::string, std::string > &opts)

virtual void	create_submodule_Linear (const std::string &name, const std::map< std::string, std::string > &opts)

virtual void	create_submodule_Dropout (const std::string &name, const std::map< std::string, std::string > &opts)

virtual void	create_submodule_DeepBiaffineAttentionDecoder (const std::string &name, const std::map< std::string, std::string > &opts)

virtual void	create_submodule_DeepBiaffineAttentionLabelDecoder (const std::string &name, const std::map< std::string, std::string > &opts)

virtual void	init_rnns ()

Static Protected Member Functions
static std::string	generate_script (const std::vector< nets::embd_descr_t > &embd_descr, const std::vector< nets::rnn_descr_t > &rnn_descr, const std::vector< nets::deep_biaffine_attention_descr_t > &decoder_descr, const std::vector< std::string > &output_names, bool input_includes_root=false, int64_t num_labels=0)

Static Protected Member Functions inherited from deeplima::nets::BiRnnClassifierImpl
static std::string	generate_script (const std::vector< embd_descr_t > &embd_descr, const std::vector< rnn_descr_t > &rnn_descr, const std::vector< std::string > &output_names, const std::vector< uint32_t > &classes, float input_dropout_prob)

Protected Attributes
size_t	m_workers

int64_t	m_num_labels = 0

std::vector< std::string >	m_rel_class_names

std::vector< std::string >	m_input_class_names

DictsHolder	m_input_classes

std::vector< std::string >	m_output_class_names

DictsHolder	m_output_classes

std::string	m_embd_fn

Protected Attributes inherited from deeplima::nets::BiRnnClassifierImpl
std::vector< embd_descr_t >	m_embd_descr

Protected Attributes inherited from deeplima::nets::StaticGraphImpl
std::map< std::string, std::vector< size_t > >	m_exec_plans

DictsHolder	m_dicts

std::string	m_script

std::map< std::string, std::string >	m_tags

std::vector< torch::nn::Embedding >	m_embedding

std::vector< torch::nn::LSTM >	m_lstm

std::vector< torch::nn::Linear >	m_linear

std::vector< torch::nn::Dropout >	m_dropout

std::vector< deeplima::nets::torch_modules::DeepBiaffineAttentionDecoder >	m_deep_biaffine_attention_decoder

std::vector< deeplima::nets::torch_modules::DeepBiaffineAttentionLabelDecoder >	m_deep_biaffine_attention_label_decoder

std::map< std::string, module_ref_t >	m_modules

std::set< std::string >	m_args

std::map< std::string, size_t >	m_tensor_name_to_idx

std::vector< op_t >	m_ops

std::map< size_t, size_t >	m_outidx_to_opidx

Detailed Description

Definition at line 21 of file birnn_and_deep_biaffine_attention.h.

Member Typedef Documentation

◆ dicts_holder_t

typedef DictsHolder deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::dicts_holder_t

Definition at line 25 of file birnn_and_deep_biaffine_attention.h.

◆ tensor_t

typedef torch::Tensor deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::tensor_t

Definition at line 24 of file birnn_and_deep_biaffine_attention.h.

Constructor & Destructor Documentation

◆ BiRnnAndDeepBiaffineAttentionImpl() [1/2]

deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::BiRnnAndDeepBiaffineAttentionImpl ( )

inline

Definition at line 27 of file birnn_and_deep_biaffine_attention.h.

◆ BiRnnAndDeepBiaffineAttentionImpl() [2/2]

deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::BiRnnAndDeepBiaffineAttentionImpl	(	DictsHolder &&	dicts,
		const std::vector< nets::embd_descr_t > &	embd_descr,
		const std::vector< nets::rnn_descr_t > &	rnn_descr,
		const std::vector< nets::deep_biaffine_attention_descr_t > &	decoder_descr,
		const std::vector< std::string > &	output_names,
		DictsHolder &&	classes,
		const std::string &	embd_fn,
		bool	input_includes_root,
		int64_t	num_labels = `0`,
		const std::vector< std::string > &	rel_class_names = `{}`
	)

inline

Definition at line 32 of file birnn_and_deep_biaffine_attention.h.

Member Function Documentation

◆ evaluate() [1/2]

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::evaluate	(	const std::vector< std::string > &	output_names,
		const torch::Tensor &	trainable_input,
		const torch::Tensor &	nontrainable_input,
		const torch::Tensor &	gold,
		nets::epoch_stat_t &	stat,
		const torch::Device &	device
	)

protected

Definition at line 475 of file birnn_and_deep_biaffine_attention.cpp.

◆ evaluate() [2/2]

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::evaluate	(	const std::vector< std::string > &	output_names,
		std::shared_ptr< BatchIterator >	dataset_iterator,
		nets::epoch_stat_t &	stat,
		const torch::Device &	device = `torch::Device(torch::kCPU)`
	)

Definition at line 440 of file birnn_and_deep_biaffine_attention.cpp.

◆ generate_script()

string deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::generate_script	(	const std::vector< nets::embd_descr_t > &	embd_descr,
		const std::vector< nets::rnn_descr_t > &	rnn_descr,
		const std::vector< nets::deep_biaffine_attention_descr_t > &	decoder_descr,
		const std::vector< std::string > &	output_names,
		bool	input_includes_root = `false`,
		int64_t	num_labels = `0`
	)

staticprotected

Definition at line 21 of file birnn_and_deep_biaffine_attention_script_generator.cpp.

◆ get_classes()

const DictsHolder & deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::get_classes ( ) const

inline

Definition at line 96 of file birnn_and_deep_biaffine_attention.h.

◆ get_embd_fn()

const std::string & deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::get_embd_fn ( size_t idx ) const

inline

Definition at line 117 of file birnn_and_deep_biaffine_attention.h.

◆ get_input_class_names()

const std::vector< std::string > & deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::get_input_class_names ( ) const

inline

Definition at line 106 of file birnn_and_deep_biaffine_attention.h.

◆ get_output_class_names()

const std::vector< std::string > & deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::get_output_class_names ( ) const

inline

Definition at line 101 of file birnn_and_deep_biaffine_attention.h.

◆ get_rel_class_names()

const std::vector< std::string > & deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::get_rel_class_names ( ) const

inline

Definition at line 112 of file birnn_and_deep_biaffine_attention.h.

◆ init_new_worker()

size_t deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::init_new_worker ( size_t )

inline

Definition at line 68 of file birnn_and_deep_biaffine_attention.h.

◆ load() [1/2]

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::load ( const std::string & fn )

inline

Definition at line 63 of file birnn_and_deep_biaffine_attention.h.

◆ load() [2/2]

virtual void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::load ( torch::serialize::InputArchive & archive )

virtual

Reimplemented from deeplima::nets::BiRnnClassifierImpl.

◆ predict()

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::predict	(	size_t	worker_id,
		const torch::Tensor &	inputs,
		int64_t	input_begin,
		int64_t	input_end,
		int64_t	output_begin,
		int64_t	output_end,
		std::shared_ptr< StdMatrix< uint8_t > > &	output,
		const std::vector< std::string > &	outputs_names,
		const torch::Device &	device = `torch::Device(torch::kCPU)`
	)

Definition at line 538 of file birnn_and_deep_biaffine_attention.cpp.

◆ save()

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::save ( torch::serialize::OutputArchive & archive ) const

virtual

Reimplemented from deeplima::nets::BiRnnClassifierImpl.

Definition at line 161 of file birnn_and_deep_biaffine_attention.cpp.

◆ train()

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::train	(	const train_params_graph_dp_t &	params,
		const std::vector< std::string > &	output_names,
		const IterableDataSet &	train_batches,
		const IterableDataSet &	eval_batches,
		torch::optim::Optimizer &	opt,
		double &	best_eval_accuracy,
		const torch::Device &	device = `torch::Device(torch::kCPU)`
	)

Definition at line 217 of file birnn_and_deep_biaffine_attention.cpp.

◆ train_batch()

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::train_batch	(	size_t	batch_size,
		size_t	seq_len,
		const std::vector< std::string > &	output_names,
		const torch::Tensor &	trainable_input,
		const torch::Tensor &	nontrainable_input,
		const torch::Tensor &	gold,
		torch::optim::Optimizer &	opt,
		nets::epoch_stat_t &	stat,
		const torch::Device &	device
	)

protected

Definition at line 370 of file birnn_and_deep_biaffine_attention.cpp.

◆ train_epoch()

void deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::train_epoch	(	size_t	batch_size,
		size_t	seq_len,
		const std::vector< std::string > &	output_names,
		std::shared_ptr< BatchIterator >	train_iterator,
		torch::optim::Optimizer &	opt,
		nets::epoch_stat_t &	stat,
		const torch::Device &	device
	)

protected

Definition at line 339 of file birnn_and_deep_biaffine_attention.cpp.

Member Data Documentation

◆ m_embd_fn

std::string deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_embd_fn

protected

Definition at line 164 of file birnn_and_deep_biaffine_attention.h.

◆ m_input_class_names

std::vector<std::string> deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_input_class_names

protected

Definition at line 160 of file birnn_and_deep_biaffine_attention.h.

◆ m_input_classes

DictsHolder deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_input_classes

protected

Definition at line 161 of file birnn_and_deep_biaffine_attention.h.

◆ m_num_labels

int64_t deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_num_labels = 0

protected

Definition at line 158 of file birnn_and_deep_biaffine_attention.h.

◆ m_output_class_names

std::vector<std::string> deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_output_class_names

protected

Definition at line 162 of file birnn_and_deep_biaffine_attention.h.

◆ m_output_classes

DictsHolder deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_output_classes

protected

Definition at line 163 of file birnn_and_deep_biaffine_attention.h.

◆ m_rel_class_names

std::vector<std::string> deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_rel_class_names

protected

Definition at line 159 of file birnn_and_deep_biaffine_attention.h.

◆ m_workers

size_t deeplima::graph_dp::train::BiRnnAndDeepBiaffineAttentionImpl::m_workers

protected

Definition at line 157 of file birnn_and_deep_biaffine_attention.h.

The documentation for this class was generated from the following files:

deeplima/libs/tasks/graph_dp/model/birnn_and_deep_biaffine_attention.h
deeplima/libs/tasks/graph_dp/model/birnn_and_deep_biaffine_attention.cpp
deeplima/libs/tasks/graph_dp/model/birnn_and_deep_biaffine_attention_script_generator.cpp

Public Types

Public Member Functions

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ dicts_holder_t

◆ tensor_t

Constructor & Destructor Documentation

◆ BiRnnAndDeepBiaffineAttentionImpl() [1/2]

◆ BiRnnAndDeepBiaffineAttentionImpl() [2/2]

Member Function Documentation

◆ evaluate() [1/2]

◆ evaluate() [2/2]

◆ generate_script()

◆ get_classes()

◆ get_embd_fn()

◆ get_input_class_names()

◆ get_output_class_names()

◆ get_rel_class_names()

◆ init_new_worker()

◆ load() [1/2]

◆ load() [2/2]

◆ predict()

◆ save()

◆ train()

◆ train_batch()

◆ train_epoch()

Member Data Documentation

◆ m_embd_fn

◆ m_input_class_names

◆ m_input_classes

◆ m_num_labels

◆ m_output_class_names

◆ m_output_classes

◆ m_rel_class_names

◆ m_workers