diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py index 38d24007..a424f3f4 100644 --- a/pytorch_lightning/trainer/trainer.py +++ b/pytorch_lightning/trainer/trainer.py @@ -94,15 +94,63 @@ class Trainer(TrainerIOMixin, Customize every aspect of training via flags Args: - logger (:class:`.Logger`): Logger for experiment tracking - example: - >>> asd - checkpoint_callback (:class:`CheckpointCallback`): Callback for checkpointing + logger (:class:`.Logger`): Logger for experiment tracking. + Example:: + from pytorch_lightning.logging import TensorBoardLogger + + # default logger used by trainer + logger = TensorBoardLogger( + save_dir=os.getcwd(), + version=self.slurm_job_id, + name='lightning_logs' + ) + + Trainer(logger=logger) + checkpoint_callback (:class:`CheckpointCallback`): Callback for checkpointing. + Example:: + from pytorch_lightning.callbacks import ModelCheckpoint + + # default used by the Trainer + checkpoint_callback = ModelCheckpoint( + filepath=os.getcwd(), + save_best_only=True, + verbose=True, + monitor='val_loss', + mode='min', + prefix='' + ) + + trainer = Trainer(checkpoint_callback=checkpoint_callback) early_stop_callback (:class:`.EarlyStopping`): Callback for early stopping - default_save_path (str): Default path for logs+weights if no logger/ckpt_callback passed - gradient_clip_val (int): 0 means don't clip. - gradient_clip (int): 0 means don't clip. Deprecated. - process_position (int): shown in the tqdm bar + Example:: + from pytorch_lightning.callbacks import EarlyStopping + + # default used by the Trainer + early_stop_callback = EarlyStopping( + monitor='val_loss', + patience=3, + verbose=True, + mode='min' + ) + + trainer = Trainer(early_stop_callback=early_stop_callback) + default_save_path (str): Default path for logs and weights when no logger/ckpt_callback passed + Example:: + # default used by the Trainer + trainer = Trainer(default_save_path=os.getcwd()) + gradient_clip_val (float): 0 means don't clip. + Example:: + # default used by the Trainer + trainer = Trainer(gradient_clip_val=0.0) + gradient_clip (int): + .. deprecated:: 0.5.0 + Use `gradient_clip_val` instead. + + process_position (int): orders the tqdm bar when running multiple models on same machine. + Example:: + # default used by the Trainer + trainer = Trainer(process_position=0) + num_nodes (int): number of GPU nodes """ # :param list|str|int gpus: int. (ie: 2 gpus) OR list to specify which GPUs [0, 1] OR '0,1'