FitLoop

class pytorch_lightning.loops.FitLoop(min_epochs=1, max_epochs=1000)[source]

Bases: abc.ABC, Generic[pytorch_lightning.loops.base.T]

This Loop iterates over the epochs to run the training.

Parameters

min_epochs (Optional[int]) – The minimum number of epochs
max_epochs (int) – The maximum number of epochs, can be set -1 to turn this limit off

advance()[source]

Runs one whole epoch.

connect(epoch_loop)[source]: Connects a training epoch loop to this fit loop.

on_advance_end()[source]

Hook to be called each time after advance is called.

on_advance_start()[source]

Prepares the dataloader for training and calls the hooks on_epoch_start and on_train_epoch_start

on_run_end()[source]

Calls the on_train_end hook.

on_run_start()[source]

Calls the on_train_start hook.

Resets the internal state of this loop.

teardown()[source]

Use to release memory etc.

property batch_idx: int: Returns the current batch index (within this epoch)

property done: bool

Evaluates when to leave the loop.

Returns True if trainer.should_stop was set (e.g. by early stopping) or if the maximum number of steps or epochs is reached.

property running_loss: pytorch_lightning.trainer.supporters.TensorRunningAccum: Returns the running loss.

property skip: bool: Whether we should skip the training and immediately return from the call to run().

property split_idx: int: Returns the index of the current batch split (within the current batch) for bptt.

property total_batch_idx: int: Returns the current batch index (across epochs)