Shortcuts

TrainProgressMonitor

class torchtnt.framework.callbacks.TrainProgressMonitor(loggers: Union[MetricLogger, List[MetricLogger]])

A callback which logs training progress in terms of steps vs epochs. This is helpful to visualize when the end of data occurs across epochs, especially for iterable datasets. This callback writes to the logger at the beginning of training, and at the end of every epoch.

Parameters:loggers – Either a torchtnt.loggers.logger.MetricLogger or list of torchtnt.loggers.logger.MetricLogger
on_train_epoch_end(state: State, unit: TrainUnit[TTrainData]) None

Hook called after a train epoch ends.

on_train_start(state: State, unit: TrainUnit[TTrainData]) None

Hook called before training starts.

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources