Fixed other things due to reverted commits

ignite/contrib/handlers/__init__.py

@@ -1,6 +1,5 @@
 from ignite.contrib.handlers.clearml_logger import ClearMLLogger
 from ignite.contrib.handlers.custom_events import CustomPeriodicEvent
-from ignite.contrib.handlers.lr_finder import FastaiLRFinder
 from ignite.contrib.handlers.mlflow_logger import MLflowLogger
 from ignite.contrib.handlers.neptune_logger import NeptuneLogger
 from ignite.contrib.handlers.polyaxon_logger import PolyaxonLogger

ignite/engine/engine.py

@@ -724,7 +724,13 @@ def load_state_dict(self, state_dict: Mapping) -> None:
 
     @staticmethod
     def _is_done(state: State) -> bool:
-        return state.iteration == state.epoch_length * state.max_epochs  # type: ignore[operator]
+        is_done_count = (
+            state.epoch_length is not None
+            and state.max_epochs is not None
+            and state.iteration >= state.epoch_length * state.max_epochs
+        )
+        is_done_epochs = state.max_epochs is not None and state.epoch >= state.max_epochs
+        return is_done_count or is_done_epochs
 
     def set_data(self, data: Union[Iterable, DataLoader]) -> None:
         """Method to set data. After calling the method the next batch passed to `processing_function` is
@@ -956,7 +962,6 @@ def _internal_run_as_gen(self) -> Generator:
                     self.state.times[Events.EPOCH_COMPLETED.name] = epoch_time_taken
 
                     handlers_start_time = time.time()
-
                     self._fire_event(Events.EPOCH_COMPLETED)
                     epoch_time_taken += time.time() - handlers_start_time
                     # update time wrt handlers
@@ -1039,13 +1044,8 @@ def _run_once_on_dataset_as_gen(self) -> Generator[State, None, float]:
 
                     # Should exit while loop if we can not iterate
                     if should_exit:
-                        if not self._is_done(self.state):
-                            total_iters = (
-                                self.state.epoch_length * self.state.max_epochs
-                                if self.state.max_epochs is not None
-                                else self.state.max_iters
-                            )
-
+                        if not self._is_done(self.state) and self.state.max_epochs is not None:
+                            total_iters = self.state.epoch_length * self.state.max_epochs
                             warnings.warn(
                                 "Data iterator can not provide data anymore but required total number of "
                                 "iterations to run is not reached. "
@@ -1072,10 +1072,6 @@ def _run_once_on_dataset_as_gen(self) -> Generator[State, None, float]:
                 if self.state.epoch_length is not None and iter_counter == self.state.epoch_length:
                     break
 
-                if self.state.max_iters is not None and self.state.iteration == self.state.max_iters:
-                    self.should_terminate = True
-                    raise _EngineTerminateException()
-
         except _EngineTerminateSingleEpochException:
             self._fire_event(Events.TERMINATE_SINGLE_EPOCH, iter_counter=iter_counter)
             self.should_terminate_single_epoch = False
@@ -1191,19 +1187,12 @@ def _run_once_on_dataset_legacy(self) -> float:
                     if self.state.epoch_length is None:
                         # Define epoch length and stop the epoch
                         self.state.epoch_length = iter_counter
-                        if self.state.max_iters is not None:
-                            self.state.max_epochs = math.ceil(self.state.max_iters / self.state.epoch_length)
                         break
 
                     # Should exit while loop if we can not iterate
                     if should_exit:
-                        if not self._is_done(self.state):
-                            total_iters = (
-                                self.state.epoch_length * self.state.max_epochs
-                                if self.state.max_epochs is not None
-                                else self.state.max_iters
-                            )
-
+                        if not self._is_done(self.state) and self.state.max_epochs is not None:
+                            total_iters = self.state.epoch_length * self.state.max_epochs
                             warnings.warn(
                                 "Data iterator can not provide data anymore but required total number of "
                                 "iterations to run is not reached. "
@@ -1230,10 +1219,6 @@ def _run_once_on_dataset_legacy(self) -> float:
                 if self.state.epoch_length is not None and iter_counter == self.state.epoch_length:
                     break
 
-                if self.state.max_iters is not None and self.state.iteration == self.state.max_iters:
-                    self.should_terminate = True
-                    raise _EngineTerminateException()
-
         except _EngineTerminateSingleEpochException:
             self._fire_event(Events.TERMINATE_SINGLE_EPOCH, iter_counter=iter_counter)
             self.should_terminate_single_epoch = False

ignite/engine/events.py

@@ -152,7 +152,7 @@ def __init__(self, *args: Any, **kwargs: Any) -> None:
         )
 
 
-class EventEnum(CallableEventWithFilter, Enum):  # type: ignore[misc]
+class EventEnum(CallableEventWithFilter, Enum):
     """Base class for all :class:`~ignite.engine.events.Events`. User defined custom events should also inherit
     this class.
 

ignite/handlers/checkpoint.py

@@ -962,7 +962,7 @@ def __init__(
         self,
         dirname: Union[str, Path],
         filename_prefix: str = "",
-        save_interval: Optional[Callable] = None,
+        save_interval: Optional[int] = None,
         score_function: Optional[Callable] = None,
         score_name: Optional[str] = None,
         n_saved: Union[int, None] = 1,

ignite/handlers/lr_finder.py

@@ -105,7 +105,6 @@ def _run(
             max_iter = trainer.state.epoch_length * trainer.state.max_epochs  # type: ignore[operator]
             if max_iter < num_iter:
                 max_iter = num_iter
-                trainer.state.max_iters = num_iter
                 trainer.state.max_epochs = ceil(num_iter / trainer.state.epoch_length)  # type: ignore[operator]
 
         if not trainer.has_event_handler(self._reached_num_iterations):

mypy.ini

@@ -77,3 +77,6 @@ ignore_missing_imports = True
 
 [mypy-torchvision.*]
 ignore_missing_imports = True
+
+[mypy-ignite.contrib.handlers.custom_events]
+ignore_errors = True

tests/ignite/engine/test_engine.py

@@ -1029,47 +1029,6 @@ def switch_dataloader():
 
         trainer.run(data1, max_epochs=10)
 
-    def test_run_with_max_iters(self):
-        max_iters = 8
-        engine = Engine(lambda e, b: 1)
-        engine.run([0] * 20, max_iters=max_iters)
-        assert engine.state.iteration == max_iters
-        assert engine.state.max_iters == max_iters
-
-    def test_run_with_max_iters_greater_than_epoch_length(self):
-        max_iters = 73
-        engine = Engine(lambda e, b: 1)
-        engine.run([0] * 20, max_iters=max_iters)
-        assert engine.state.iteration == max_iters
-
-    def test_run_with_invalid_max_iters_and_max_epoch(self):
-        max_iters = 12
-        max_epochs = 2
-        engine = Engine(lambda e, b: 1)
-        with pytest.raises(
-            ValueError,
-            match=r"Arguments max_iters and max_epochs are mutually exclusive."
-            "Please provide only max_epochs or max_iters.",
-        ):
-            engine.run([0] * 20, max_iters=max_iters, max_epochs=max_epochs)
-
-    def test_epoch_events_fired_max_iters(self):
-        max_iters = 32
-        engine = Engine(lambda e, b: 1)
-
-        @engine.on(Events.EPOCH_COMPLETED)
-        def fired_event(engine):
-            assert engine.state.iteration % engine.state.epoch_length == 0
-
-        engine.run([0] * 10, max_iters=max_iters)
-
-    def test_is_done_with_max_iters(self):
-        state = State(iteration=100, epoch=1, max_epochs=3, epoch_length=100, max_iters=250)
-        assert not Engine._is_done(state)
-
-        state = State(iteration=250, epoch=1, max_epochs=3, epoch_length=100, max_iters=250)
-        assert Engine._is_done(state)
-
     @pytest.mark.skipif(torch.cuda.device_count() < 1, reason="Skip if no GPU")
     def test_batch_is_released_before_new_one_is_loaded_on_cuda(self):
         torch.cuda.empty_cache()

tests/ignite/handlers/test_lr_finder.py

@@ -309,7 +309,7 @@ def test_num_iter_is_not_enough(lr_finder, to_save, dummy_engine, dataloader):
             trainer_with_finder.run(dataloader)
         assert_output_sizes(lr_finder, dummy_engine)
         assert dummy_engine.state.iteration != len(dataloader)
-        assert dummy_engine.state.iteration == 150
+        assert dummy_engine.state.iteration == 150 + 1
 
 
 def test_detach_terminates(lr_finder, to_save, dummy_engine, dataloader):