pyabsa.tasks._Archive.ProteinRegression
Subpackages
pyabsa.tasks._Archive.ProteinRegression.configuration
pyabsa.tasks._Archive.ProteinRegression.dataset_utils
pyabsa.tasks._Archive.ProteinRegression.instructor
pyabsa.tasks._Archive.ProteinRegression.models
pyabsa.tasks._Archive.ProteinRegression.prediction
pyabsa.tasks._Archive.ProteinRegression.trainer
Package Contents
Classes
Trainer class for training PyABSA models |
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Simple object for storing attributes. |
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Built-in mutable sequence. |
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Built-in mutable sequence. |
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Protein Sequence-based Regression Dataset Lists |
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Protein Sequence-based Regression Dataset Lists |
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- class pyabsa.tasks._Archive.ProteinRegression.ProteinRTrainer(config: pyabsa.tasks._Archive.ProteinRegression.configuration.proteinr_configuration.ProteinRConfigManager = None, dataset=None, from_checkpoint: str = None, checkpoint_save_mode: int = ModelSaveOption.SAVE_MODEL_STATE_DICT, auto_device: Union[bool, str] = DeviceTypeOption.AUTO, path_to_save=None, load_aug=False)[source]
Bases:
pyabsa.framework.trainer_class.trainer_template.Trainer
Trainer class for training PyABSA models
- class pyabsa.tasks._Archive.ProteinRegression.ProteinRConfigManager(args, **kwargs)[source]
Bases:
pyabsa.framework.configuration_class.configuration_template.ConfigManager
Simple object for storing attributes.
Implements equality by attribute names and values, and provides a simple string representation.
- static set_proteinr_config(configType: str, newitem: dict)
- static set_proteinr_config_template(newitem)
- static set_proteinr_config_base(newitem)
- static set_proteinr_config_english(newitem)
- static set_proteinr_config_chinese(newitem)
- static set_proteinr_config_multilingual(newitem)
- static set_proteinr_config_glove(newitem)
- static get_proteinr_config_template()
- static get_proteinr_config_base()
- static get_proteinr_config_english()
- static get_proteinr_config_chinese()
- static get_proteinr_config_multilingual()
- static get_proteinr_config_glove()
- class pyabsa.tasks._Archive.ProteinRegression.BERTProteinRModelList[source]
Bases:
list
Built-in mutable sequence.
If no argument is given, the constructor creates a new empty list. The argument must be an iterable if specified.
- BERT_MLP
- class pyabsa.tasks._Archive.ProteinRegression.GloVeProteinRModelList[source]
Bases:
list
Built-in mutable sequence.
If no argument is given, the constructor creates a new empty list. The argument must be an iterable if specified.
- CNN
- LSTM
- Transformer
- MHSA
- class pyabsa.tasks._Archive.ProteinRegression.ProteinRDatasetList[source]
Bases:
list
Protein Sequence-based Regression Dataset Lists
- class pyabsa.tasks._Archive.ProteinRegression.ProteinRegressionDatasetList[source]
Bases:
list
Protein Sequence-based Regression Dataset Lists
- class pyabsa.tasks._Archive.ProteinRegression.ProteinRegressor(checkpoint=None, **kwargs)[source]
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)
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. :return: prediction result.
- predict(text: Union[str, list] = None, print_result=True, ignore_error=True, **kwargs)
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. :return: prediction 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.ProteinRegression.Predictor(checkpoint=None, **kwargs)[source]
Bases:
ProteinRegressor