pyabsa.tasks._Archive.RNAClassification.prediction.rna_classifier

Module Contents

Classes

RNAClassifier
Predictor

class pyabsa.tasks._Archive.RNAClassification.prediction.rna_classifier.RNAClassifier(checkpoint=None, cal_perplexity=False, **kwargs)

Bases: pyabsa.framework.prediction_class.predictor_template.InferenceModel

task_code

_log_write_args()

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

Runs inference on a batch of data.

Parameters:

• target_file (-) – str or Path. Path to the target file.

• print_result (-) – bool. Whether to print the result.

• save_result (-) – bool. Whether to save the result.

• ignore_error (-) – bool. Whether to ignore errors.

• kwargs (-) – dict. Additional keyword arguments.

Returns:

list. List of predictions.

Return type:

• result

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

Runs inference on a single sample.

Parameters:

• text (-) – str. The text to predict.

• print_result (-) – bool. Whether to print the result.

• ignore_error (-) – bool. Whether to ignore errors.

• kwargs (-) – dict. Additional keyword arguments.

Returns:

list. List of predictions.

Return type:

• result

_run_prediction(save_path=None, print_result=True)

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._Archive.RNAClassification.prediction.rna_classifier.Predictor(checkpoint=None, cal_perplexity=False, **kwargs)

Bases: RNAClassifier