(self, checkpoint)

(data, lengths, is_right_aligned=False)

( name, level=logging.DEBUG, format='[%(asctime)s] [%(levelname)s]: %(message)s',

(cls, inter_json_path, max_sequence_length, sampler_type, is_extended=False)

(self)

(self, initializer_range)

(seed)

(self)

()

(self)

(self)

( self, positive_prefix, negative_prefix, output_prefix=None

(self, events, lengths)

(self, *args, **kwargs)

()

()

(self, batch)

(self, inputs, pred_prefix, labels_prefix)

(self, inputs, pred_prefix, labels_prefix)

(self, inputs, pred_prefix, labels_prefix)

(self, inputs, pred_prefix, labels_prefix)

(self, key, value, step_num, prefix)

(self, step_num)

(self, input_ids: torch.LongTensor, scores: torch.FloatTensor)

(self, index)

(self, index)

( self, experiment_name, logs_dir='../tensorboard_logs', use_t

(self, dataset, prediction_type, max_sequence_length)

(self, dataset, max_sequence_length)

( self, train_sampler, validation_sampler, test_sampler,

(self, semantic_ids=None, sem_id_len=None, user_ids_count=None)

(self, k)

(self, k, codebook_size, num_codebooks)

(self, k)

(self, k, codebook_size, num_codebooks)

(self, tensorboard_writer, on_step)

( self, tensorboard_writer, step_name, model, data

( self, experiment_name, train_dataloader, validation_dataload

(self, num_codebooks, codebook_size, index_path, num_beams, visited_items)

( self, embedding_dim, codebook_size, sem_id_len,

( self, num_items, max_sequence_length, embedding_dim,

(self, predictions_prefix, output_prefix=None)

(self)

(self)

(self, sample)

(self, sample)

(cls, mapping_path, sem_id_len, user_ids_count)

(self)

(self, inputs)

(self, inputs)

(self, inputs)

(self, inputs)

(name, **kwargs)

(self)

(self)