pyabsa.tasks.RNAClassification

Subpackages

• pyabsa.tasks.RNAClassification.configuration
  • pyabsa.tasks.RNAClassification.configuration.rnac_configuration
• pyabsa.tasks.RNAClassification.dataset_utils
  • pyabsa.tasks.RNAClassification.dataset_utils.data_utils_for_inference
  • pyabsa.tasks.RNAClassification.dataset_utils.data_utils_for_training
  • pyabsa.tasks.RNAClassification.dataset_utils.dataset_list
• pyabsa.tasks.RNAClassification.instructor
  • pyabsa.tasks.RNAClassification.instructor.rnac_instructor
• pyabsa.tasks.RNAClassification.models
  • pyabsa.tasks.RNAClassification.models.__classic__
    • pyabsa.tasks.RNAClassification.models.__classic__.cnn
    • pyabsa.tasks.RNAClassification.models.__classic__.lstm
    • pyabsa.tasks.RNAClassification.models.__classic__.mhsa
    • pyabsa.tasks.RNAClassification.models.__classic__.transformer
  • pyabsa.tasks.RNAClassification.models.__plm__
    • pyabsa.tasks.RNAClassification.models.__plm__.bert
• pyabsa.tasks.RNAClassification.prediction
  • pyabsa.tasks.RNAClassification.prediction.rna_classifier
• pyabsa.tasks.RNAClassification.trainer
  • pyabsa.tasks.RNAClassification.trainer.rnac_trainer

Package Contents

Classes

RNACTrainer	Trainer class for training PyABSA models
RNACConfigManager	Simple object for storing attributes.
BERTRNACModelList	Built-in mutable sequence.
GloVeRNACModelList	Built-in mutable sequence.
RNACDatasetList	A list of available RNA datasets.
RNAClassificationDatasetList	A list of available RNA datasets.
RNAClassifier
Predictor

class pyabsa.tasks.RNAClassification.RNACTrainer(config: pyabsa.tasks.RNAClassification.configuration.rnac_configuration.RNACConfigManager = None, dataset=None, from_checkpoint: str = None, checkpoint_save_mode: int = ModelSaveOption.SAVE_MODEL_STATE_DICT, auto_device: bool | str = DeviceTypeOption.AUTO, path_to_save=None, load_aug=False)

Bases: pyabsa.framework.trainer_class.trainer_template.Trainer

Trainer class for training PyABSA models

class pyabsa.tasks.RNAClassification.RNACConfigManager(args, **kwargs)

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_rnac_config(configType: str, newitem: dict)

static set_rnac_config_template(newitem)

static set_rnac_config_base(newitem)

static set_rnac_config_english(newitem)

static set_rnac_config_chinese(newitem)

static set_rnac_config_multilingual(newitem)

static set_rnac_config_glove(newitem)

static get_rnac_config_template()

static get_rnac_config_base()

static get_rnac_config_english()

static get_rnac_config_chinese()

static get_rnac_config_multilingual()

static get_rnac_config_glove()

class pyabsa.tasks.RNAClassification.BERTRNACModelList

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

BERT

class pyabsa.tasks.RNAClassification.GloVeRNACModelList

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.RNAClassification.RNACDatasetList

Bases: list

A list of available RNA datasets.

class pyabsa.tasks.RNAClassification.RNAClassificationDatasetList

Bases: RNACDatasetList

A list of available RNA datasets.

class pyabsa.tasks.RNAClassification.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)

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: 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.

_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.RNAClassification.Predictor(checkpoint=None, cal_perplexity=False, **kwargs)

Bases: RNAClassifier