actableai.third_parties.spanABSA.span_absa_helper.ExtractInferenceFeature(source_data, tokens, input_ids, input_mask, segment_ids, token_to_orig_map)¶Bases: object
actableai.third_parties.spanABSA.span_absa_helper.PolarityClassifierFeature(source_data, tokens, input_ids, input_mask, segment_ids, start_indexes, end_indexes, start_indexes_padding, end_indexes_padding)¶Bases: object
actableai.third_parties.spanABSA.span_absa_helper.SourceData(sentence, tokenizer)¶Bases: object
actableai.third_parties.spanABSA.span_absa_helper.convert_source_data_to_feature(source_data, tokenizer, max_seq_length)¶actableai.third_parties.spanABSA.span_absa_helper.detect(sentence, tokenizer, extract_model, cls_model, device)¶actableai.third_parties.spanABSA.span_absa_helper.extract_inference_result_to_feature(extract_inference_results, max_term_num)¶actableai.third_parties.spanABSA.span_absa_helper.list_object(obj)¶actableai.third_parties.spanABSA.span_absa_helper.load_model(Model, bert_config, bert_init_model_dir, model_dir, device, n_gpu)¶actableai.third_parties.spanABSA.span_absa_helper.predict_cls(model, feature: actableai.third_parties.spanABSA.span_absa_helper.PolarityClassifierFeature, device)¶actableai.third_parties.spanABSA.span_absa_helper.predict_extract_inference(model, feature: actableai.third_parties.spanABSA.span_absa_helper.ExtractInferenceFeature, device, n_best_size=20, max_answer_length=12, logit_threshold=7.5, use_heuristics=True)¶