EvaluationEpochLoop
- class pytorch_lightning.loops.epoch.EvaluationEpochLoop[source]
Bases:
pytorch_lightning.loops.base.Loop
This is the loop performing the evaluation.
It mainly loops over the given dataloader and runs the validation or test step (depending on the trainer’s current state).
- advance(data_fetcher, dl_max_batches, kwargs)[source]
Calls the evaluation step with the corresponding hooks and updates the logger connector.
- Parameters
data_fetcher (
AbstractDataFetcher
) – iterator over the dataloaderdl_max_batches (
int
) – maximum number of batches the dataloader can producekwargs (
OrderedDict
) – the kwargs passed down to the hooks.
- Raises
StopIteration – If the current batch is None
- Return type
- on_load_checkpoint(state_dict)[source]
Called when loading a model checkpoint, use to reload loop state.
- Return type
- on_run_end()[source]
Returns the outputs of the whole run.
- on_run_start(data_fetcher, dl_max_batches, kwargs)[source]
Adds the passed arguments to the loop’s state if necessary.
- Parameters
data_fetcher (
AbstractDataFetcher
) – the current data_fetcher wrapping the dataloaderdl_max_batches (
int
) – maximum number of batches the dataloader can producekwargs (
OrderedDict
) – the kwargs passed down to the hooks.
- Return type
- on_save_checkpoint()[source]
Called when saving a model checkpoint, use to persist loop state.
- Return type
- Returns
The current loop state.