pyabsa.tasks.TextAdversarialDefense.prediction.tad_classifier
Module Contents
Classes
Functions
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- pyabsa.tasks.TextAdversarialDefense.prediction.tad_classifier.init_attacker(tad_classifier, defense)[source]
- class pyabsa.tasks.TextAdversarialDefense.prediction.tad_classifier.TADTextClassifier(checkpoint=None, cal_perplexity=False, **kwargs)[source]
Bases:
pyabsa.framework.prediction_class.predictor_template.InferenceModel
- batch_infer(target_file=None, print_result=True, save_result=False, ignore_error=True, defense: str = None, **kwargs)[source]
Batch prediction on an input file. :param target_file: the path of the input file :param print_result: whether to print the prediction results to the console :param save_result: whether to save the prediction results to a file :param ignore_error: whether to ignore errors during inference :param defense: adversarial defense technique to use during inference
- infer(text: Union[str, list] = None, print_result=True, ignore_error=True, defense: str = None, **kwargs)[source]
Perform prediction on a single text or a list of texts. :param text: the text(s) to perform prediction on :param print_result: whether to print the prediction results to the console :param ignore_error: whether to ignore errors during inference :param defense: adversarial defense technique to use during inference
- batch_predict(target_file=None, print_result=True, save_result=False, ignore_error=True, defense: str = None, **kwargs)[source]
Predict 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: Union[str, list] = None, print_result=True, ignore_error=True, defense: str = None, **kwargs)[source]
Predict from a sentence or a list of sentences. param: text: the sentence or a list of 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.
- class pyabsa.tasks.TextAdversarialDefense.prediction.tad_classifier.Predictor(checkpoint=None, cal_perplexity=False, **kwargs)[source]
Bases:
TADTextClassifier