EpochBasedTrainLoop¶

class mmengine.runner.EpochBasedTrainLoop(runner, dataloader, max_epochs, val_begin=1, val_interval=1, dynamic_intervals=None)[source]¶

Loop for epoch-based training.

Parameters

runner (Runner) – A reference of runner.
dataloader (Dataloader or dict) – A dataloader object or a dict to build a dataloader.
max_epochs (int) – Total training epochs.
val_begin (int) – The epoch that begins validating. Defaults to 1.
val_interval (int) – Validation interval. Defaults to 1.
dynamic_intervals (List[Tuple[int, int]], optional) – The first element in the tuple is a milestone and the second element is a interval. The interval is used after the corresponding milestone. Defaults to None.

Return type

None

property epoch¶

Current epoch.

Type: int

property iter¶

Current iteration.

Type: int

property max_epochs¶

Total epochs to train model.

Type: int

property max_iters¶

Total iterations to train model.

Type: int

run()[source]¶

Launch training.

Return type: torch.nn.modules.module.Module

run_epoch()[source]¶

Iterate one epoch.

Return type: None

run_iter(idx, data_batch)[source]¶

Iterate one min-batch.

Parameters: data_batch (Sequence[dict]) – Batch of data from dataloader.
Return type: None