Updated logic for disabling automatic stopping

pytorch_lightning/loops/fit_loop.py

@@ -129,13 +129,9 @@ def done(self) -> bool:
         Returns True if trainer.should_stop was set (e.g. by early stopping)
         or if the maximum number of steps or epochs is reached.
         """
-        if self.max_epochs < 0 and self.max_steps is None:
-            # If max_epochs is negative and max_steps is not defined, disable automatic stopping
-            return False
-
         # TODO(@awaelchli): Move track steps inside training loop and move part of these condition inside training loop
-        stop_steps = self.max_steps is not None and self.global_step >= self.max_steps
-        stop_epochs = self.max_epochs is not None and self.current_epoch >= self.max_epochs
+        stop_steps = self.max_steps not in [None, -1] and self.global_step >= self.max_steps
+        stop_epochs = self.max_epochs not in [None, -1] and self.current_epoch >= self.max_epochs
 
         should_stop = False
         if self.trainer.should_stop:

pytorch_lightning/trainer/trainer.py

@@ -265,12 +265,15 @@ def __init__(
 
             max_epochs: Stop training once this number of epochs is reached. Disabled by default (None).
                 If both max_epochs and max_steps are not specified, defaults to ``max_epochs`` = 1000.
-                To disable automatic stopping, specify a negative integer (and leave max_steps = None).
+                To disable automatic stopping, you can set ``max_epochs = -1`` and set ``max_steps`` as ``None``
+                or ``-1``. Note that if the the ``max_time`` limit is specified, it will still be observed.
 
             min_epochs: Force training for at least these many epochs. Disabled by default (None).
                 If both min_epochs and min_steps are not specified, defaults to ``min_epochs`` = 1.
 
-            max_steps: Stop training after this number of steps. Disabled by default (None).
+            max_steps: Stop training after this number of steps. Disabled by default (None). If ``max_steps = None``
+                and ``max_epochs = None``, will default to ``max_epochs = 1000``. To override this
+                behavior, see ``max_epochs``.
 
             min_steps: Force training for at least these number of steps. Disabled by default (None).
 
@@ -378,6 +381,7 @@ def __init__(
         self.slurm_connector = SLURMConnector(self)
         self.tuner = Tuner(self)
 
+        # max_epochs won't default to 1000 if max_steps/max_time are specified (including being set to -1).
         fit_loop = FitLoop(
             min_epochs=(1 if (min_epochs is None and min_steps is None and max_time is None) else min_epochs),
             max_epochs=(1000 if (max_epochs is None and max_steps is None and max_time is None) else max_epochs),