Inheritance diagram for OpenKE.config.Trainer.Trainer:

Collaboration diagram for OpenKE.config.Trainer.Trainer:

Public Member Functions
	__init__ (self, model=None, data_loader=None, train_times=1000, alpha=0.5, use_gpu=False, opt_method="sgd", save_steps=None, checkpoint_dir=None, index_dir=None, out_path=None)

	load_entity_names (self, index_dir)

	train_one_step (self, data)

	getEntityDict (self, ent_embeddings)

	run (self, link_prediction=False, test_dataloader=None, model=None, is_analogy=False, ray=True, freq=10)

	set_model (self, model)

	to_var (self, x, use_gpu)

	set_use_gpu (self, use_gpu)

	set_alpha (self, alpha)

	set_lr_decay (self, lr_decay)

	set_weight_decay (self, weight_decay)

	set_opt_method (self, opt_method)

	set_train_times (self, train_times)

	set_save_steps (self, save_steps, checkpoint_dir=None)

	set_checkpoint_dir (self, checkpoint_dir)

Public Attributes
int	work_threads = 8

	train_times = train_times

	index_dir = index_dir

str	opt_method = opt_method

	optimizer = None

int	lr_decay = 0

int	weight_decay = 0

	alpha = alpha

	model = model

	data_loader = data_loader

	use_gpu = use_gpu

int	save_steps = save_steps

	checkpoint_dir = checkpoint_dir

	entity_names = self.load_entity_names(index_dir)

	analogies = analogy.AnalogyScorer(analogy_file="analogies.txt")

	entity_dict

Member Function Documentation

◆ getEntityDict()

OpenKE.config.Trainer.Trainer.getEntityDict	(		self,
			ent_embeddings )

Reads the entity embeddings and returns an dictionary
mapping entity names to their corresponding embeddings.

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