vis4d.pl.callbacks

Callbacks handling data related stuff (evaluation, visualization, etc).

class CallbackWrapper(callback)

Wrapper to connect vis4d callbacks to pytorch lightning callbacks.

Init class.

on_test_batch_end(trainer, pl_module, outputs, batch, batch_idx, dataloader_idx=0)

Wait for on_test_batch_end PL hook to call ‘process’.

Return type:

None

on_test_epoch_end(trainer, pl_module)

Wait for on_test_epoch_end PL hook to call ‘evaluate’.

Return type:

None

on_test_epoch_start(trainer, pl_module)

Hook to run at the start of a testing epoch.

Return type:

None

on_train_batch_end(trainer, pl_module, outputs, batch, batch_idx)

Hook to run at the end of a training batch.

Return type:

None

on_train_batch_start(trainer, pl_module, batch, batch_idx)

Called when the train batch begins.

Return type:

None

on_train_epoch_end(trainer, pl_module)

Hook to run at the end of a training epoch.

Return type:

None

on_train_epoch_start(trainer, pl_module)

Hook to run at the start of a training epoch.

Return type:

None

on_validation_batch_end(trainer, pl_module, outputs, batch, batch_idx, dataloader_idx=0)

Wait for on_validation_batch_end PL hook to call ‘process’.

Return type:

None

on_validation_epoch_end(trainer, pl_module)

Wait for on_validation_epoch_end PL hook to call ‘evaluate’.

Return type:

None

on_validation_epoch_start(trainer, pl_module)

Hook to run at the start of a validation epoch.

Return type:

None

setup(trainer, pl_module, stage)

Setup callback.

Return type:

None

class LRSchedulerCallback

Callback to configure learning rate during training.

on_train_batch_end(trainer, pl_module, outputs, batch, batch_idx)

Hook on training batch end.

Return type:

None

Modules

vis4d.pl.callbacks.callback_wrapper	Wrapper to connect PyTorch Lightning callbacks.
vis4d.pl.callbacks.scheduler	Callback to configure learning rate during training.