pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils
Module Contents
Functions
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- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.syntax_distance_alignment(tokens, dist, max_seq_len, tokenizer)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.pad_syntax_based_srd(text, dep_dist, tokenizer, config)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.prepare_input_for_apc(config, tokenizer, text_left, text_right, aspect, input_demands)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.text_to_sequence(tokenizer, text, max_seq_len)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.get_syntax_distance(text_raw, aspect, tokenizer, config)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.get_lca_ids_and_cdm_vec(config, bert_spc_indices, aspect_indices, aspect_begin, syntactical_dist=None)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.get_cdw_vec(config, bert_spc_indices, aspect_indices, aspect_begin, syntactical_dist=None)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.build_spc_mask_vec(config, text_ids)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.build_sentiment_window(examples, tokenizer, similarity_threshold, input_demands=None)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.copy_side_aspect(direct, target, source, examples, input_demands)[source]
- pyabsa.tasks.AspectPolarityClassification.dataset_utils.__lcf__.apc_utils.is_similar(s1, s2, tokenizer, similarity_threshold)[source]