pyabsa.tasks.AspectPolarityClassification.prediction.sentiment_classifier

Module Contents

Classes

SentimentClassifier
Predictor

class pyabsa.tasks.AspectPolarityClassification.prediction.sentiment_classifier.SentimentClassifier(checkpoint=None, **kwargs)

Bases: pyabsa.framework.prediction_class.predictor_template.InferenceModel

task_code

batch_infer(target_file=None, print_result=True, save_result=False, ignore_error=True, **kwargs)

A deprecated version of batch_predict method.

Parameters:

• target_file (str) – the path to the target file for inference

• print_result (bool) – whether to print the result

• save_result (bool) – whether to save the result

• ignore_error (bool) – whether to ignore the error

Returns:

a dictionary of the results

Return type:

result (dict)

infer(text: str = None, print_result=True, ignore_error=True, **kwargs)

A deprecated version of the predict method.

Parameters:

• text (str) – the text to predict

• print_result (bool) – whether to print the result

• ignore_error (bool) – whether to ignore the error

Returns:

a dictionary of the results

Return type:

result (dict)

batch_predict(target_file=None, print_result=True, save_result=False, ignore_error=True, **kwargs)

Predict the sentiment from a file of sentences. param: target_file: the file path of the sentences to be predicted. param: print_result: whether to print the result. param: save_result: whether to save the result. param: ignore_error: whether to ignore the error when predicting. param: kwargs: other parameters.

predict(text: str | list = None, print_result=True, ignore_error=True, **kwargs)

Predict the sentiment from a sentence or a list of sentences. param: text: the sentence to be predicted. param: print_result: whether to print the result. param: ignore_error: whether to ignore the error when predicting. param: kwargs: other parameters.

merge_results(results)

merge APC results have the same input text

_run_prediction(save_path=None, print_result=True, **kwargs)

This method should be implemented in the subclass for running predictions using the trained model.

Parameters:

kwargs – additional keyword arguments

Returns:

predicted labels or other prediction outputs

clear_input_samples()

class pyabsa.tasks.AspectPolarityClassification.prediction.sentiment_classifier.Predictor(checkpoint=None, **kwargs)

Bases: SentimentClassifier