mwptoolkit.trainer.abstract_trainer¶

class mwptoolkit.trainer.abstract_trainer.AbstractTrainer(config, model, dataloader, evaluator)[source]¶

Bases: object

abstract trainer

the base class of trainer class.

example of instantiation:

>>> trainer = AbstractTrainer(config, model, dataloader, evaluator)

for training:

>>> trainer.fit()

for testing:

>>> trainer.test()

for parameter searching:

>>> trainer.param_search()

Parameters

config (config) – An instance object of Config, used to record parameter information.
model (Model) – An object of deep-learning model.
dataloader (Dataloader) – dataloader object.
evaluator (Evaluator) – evaluator object.

expected that config includes these parameters below:

test_step (int): the epoch number of training after which conducts the evaluation on test.

best_folds_accuracy (list|None): when running k-fold cross validation, this keeps the accuracy of folds that already run.