EvaluationLoop

class pytorch_lightning.loops.dataloader.EvaluationLoop(verbose=True)[source]

Loops over all dataloaders for evaluation.

advance(*args, **kwargs)[source]

Performs evaluation on one single dataloader.

connect(epoch_loop)[source]

Connect the evaluation epoch loop with this loop.

on_advance_end()[source]

Hook to be called each time after advance is called.

on_advance_start(*args, **kwargs)[source]

Hook to be called each time before advance is called.

Accepts all arguments passed to :attr`run`.

on_run_end()[source]

Runs the _on_evaluation_epoch_end hook.

Return type: List[Dict[str, Union[Tensor, Dict[str, Tensor]]]]

on_run_start(*args, **kwargs)[source]

Runs the _on_evaluation_model_eval, _on_evaluation_start and _on_evaluation_epoch_start hooks.

on_skip()[source]

The function to run when run() should be skipped, determined by the condition in skip.

Resets the internal state of the loop.

teardown()[source]

Use to release memory etc.

Returns the validation or test dataloaders.

property done: bool

Returns whether all dataloaders are processed or evaluation should be skipped altogether.

property num_dataloaders: int

Returns the total number of dataloaders.

property skip: bool

Returns whether the evaluation should be skipped.