pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils

Module Contents

Functions

syntax_distance_alignment(tokens, dist, max_seq_len, ...)
pad_syntax_based_srd(text, dep_dist, tokenizer, config)
prepare_input_for_apc(config, tokenizer, text_left, ...)
text_to_sequence(tokenizer, text, max_seq_len)
get_syntax_distance(text_raw, aspect, tokenizer, config)
get_lca_ids_and_cdm_vec(config, bert_spc_indices, ...)
get_cdw_vec(config, bert_spc_indices, aspect_indices, ...)
build_spc_mask_vec(config, text_ids)
build_sentiment_window(examples, tokenizer, ...[, ...])
copy_side_aspect(direct, target, source, examples, ...)
is_similar(s1, s2, tokenizer, similarity_threshold)
configure_spacy_model(config)
calculate_dep_dist(sentence, aspect)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.syntax_distance_alignment(tokens, dist, max_seq_len, tokenizer)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.pad_syntax_based_srd(text, dep_dist, tokenizer, config)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.prepare_input_for_apc(config, tokenizer, text_left, text_right, aspect)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.text_to_sequence(tokenizer, text, max_seq_len)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.get_syntax_distance(text_raw, aspect, tokenizer, config)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.get_lca_ids_and_cdm_vec(config, bert_spc_indices, aspect_indices, aspect_begin, syntactical_dist=None)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.get_cdw_vec(config, bert_spc_indices, aspect_indices, aspect_begin, syntactical_dist=None)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.build_spc_mask_vec(config, text_ids)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.build_sentiment_window(examples, tokenizer, similarity_threshold, input_demands=None)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.copy_side_aspect(direct, target, source, examples, input_demands)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.is_similar(s1, s2, tokenizer, similarity_threshold)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.configure_spacy_model(config)

pyabsa.tasks.AspectPolarityClassification.dataset_utils.__classic__.classic_glove_apc_utils.calculate_dep_dist(sentence, aspect)