diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py index 24b6d888..38d24007 100644 --- a/pytorch_lightning/trainer/trainer.py +++ b/pytorch_lightning/trainer/trainer.py @@ -48,11 +48,6 @@ class Trainer(TrainerIOMixin, TrainerTrainLoopMixin, TrainerCallbackConfigMixin, ): - r""" - Main trainer class - - """ - def __init__( self, logger=True, @@ -95,18 +90,21 @@ class Trainer(TrainerIOMixin, resume_from_checkpoint=None, ): r""" - + Customize every aspect of training via flags + + Args: + logger (:class:`.Logger`): Logger for experiment tracking + example: + >>> asd + checkpoint_callback (:class:`CheckpointCallback`): Callback for checkpointing + 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 + num_nodes (int): number of GPU nodes """ - # Args: - # logger (ref:`Logger`): Logger for experiment tracking - # checkpoint_callback (ref:`Callback`): Callback for checkpointing - # :param early_stop_callback: Callback for early stopping - # :param str default_save_path: Default path for logs+weights if no logger/ckpt_callback passed - # :param int gradient_clip_val: 0 means don't clip. - # :param int gradient_clip: 0 means don't clip. Deprecated. - # :param process_position: shown in the tqdm bar - # :param int num_nodes: number of GPU nodes # :param list|str|int gpus: int. (ie: 2 gpus) OR list to specify which GPUs [0, 1] OR '0,1' # OR '-1' / -1 to use all available gpus # :param str log_gpu_memory: None, 'min_max', 'all'