PredictionEpochLoop
- class pytorch_lightning.loops.epoch.PredictionEpochLoop[source]
Bases:
pytorch_lightning.loops.base.Loop
Loop performing prediction on arbitrary sequentially used dataloaders.
- advance(dataloader_iter, dataloader_idx, dl_max_batches, num_dataloaders, return_predictions=False)[source]
Runs one prediction step.
- Parameters
dataloader_iter (
Iterator
) – the iterator over the current dataloaderdataloader_idx (
int
) – the index of the current dataloaderdl_max_batches (
int
) – the maximum number of batches the current loader can producenum_dataloaders (
int
) – the total number of dataloadersreturn_predictions (
bool
) – whether to return the obtained predictions
- Return type
- connect(**kwargs)[source]
Optionally connect one or multiple loops to this one.
Linked loops should form a tree.
- Return type
- on_run_end()[source]
Returns the predictions and the corresponding batch indices.
- on_run_start(dataloader_iter, dataloader_idx, dl_max_batches, num_dataloaders, return_predictions=False)[source]
Prepares the loops internal state.
- Parameters
dataloader_iter (
Iterator
) – the iterator over the current dataloaderdataloader_idx (
int
) – the index of the current dataloaderdl_max_batches (
int
) – the maximum number of batches the current loader can producenum_dataloaders (
int
) – the total number of dataloadersreturn_predictions (
bool
) – whether to return the obtained predictions
- Return type
- property done: bool
Ends prediction when the iteration count exceeds the total number of available batches.
- Return type