mypackage.MyPyroModel.train¶
-
MyPyroModel.train(max_epochs=None, use_gpu=None, train_size=0.9, validation_size=None, batch_size=128, plan_kwargs=None, **trainer_kwargs)[source]¶ Train the model.
- Parameters
- max_epochs :
int|NoneOptional[int] (default:None) Number of passes through the dataset. If None, defaults to np.min([round((20000 / n_cells) * 400), 400])
- use_gpu :
str|int|bool|NoneUnion[str,int,bool,None] (default:None) Use default GPU if available (if None or True), or index of GPU to use (if int), or name of GPU (if str), or use CPU (if False).
- train_size :
floatfloat(default:0.9) Size of training set in the range [0.0, 1.0].
- validation_size :
float|NoneOptional[float] (default:None) Size of the test set. If None, defaults to 1 - train_size. If train_size + validation_size < 1, the remaining cells belong to a test set.
- batch_size :
intint(default:128) Minibatch size to use during training.
- plan_kwargs :
dict|NoneOptional[dict] (default:None) Keyword args for
TrainingPlan. Keyword arguments passed to train() will overwrite values present in plan_kwargs, when appropriate.- **trainer_kwargs
Other keyword args for
Trainer.
- max_epochs :