myoverse.datasets.datamodule.DataModule.train_dataloader#
- DataModule.train_dataloader()[source]#
An iterable or collection of iterables specifying training samples.
For more information about multiple dataloaders, see this section.
The dataloader you return will not be reloaded unless you set :paramref:`~lightning.pytorch.trainer.trainer.Trainer.reload_dataloaders_every_n_epochs` to a positive integer.
For data processing use the following pattern:
download in
prepare_data()process and split in
setup()
However, the above are only necessary for distributed processing.
Warning
do not assign state in prepare_data
fit()prepare_data()
Note
Lightning tries to add the correct sampler for distributed and arbitrary hardware. There is no need to set it yourself.
- Return type: