Revert "Adding max_iters as an optional arg in Engine run (#1381)"

Author: vfdev-5

ignite/engine/engine.py

@@ -1,6 +1,5 @@
 import functools
 import logging
-import math
 import time
 import warnings
 import weakref
@@ -731,14 +730,13 @@ def load_state_dict(self, state_dict: Mapping) -> None:
 
     @staticmethod
     def _is_done(state: State) -> bool:
-        is_done_iters = state.max_iters is not None and state.iteration >= state.max_iters
         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_iters or is_done_count or is_done_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
@@ -780,14 +778,13 @@ def run(
         self,
         data: Optional[Iterable] = None,
         max_epochs: Optional[int] = None,
-        max_iters: Optional[int] = None,
         epoch_length: Optional[int] = None,
     ) -> State:
         """Runs the ``process_function`` over the passed data.
 
         Engine has a state and the following logic is applied in this function:
 
-        - At the first call, new state is defined by `max_epochs`, `max_iters`, `epoch_length`, if provided.
+        - At the first call, new state is defined by `max_epochs`, `epoch_length`, if provided.
           A timer for total and per-epoch time is initialized when Events.STARTED is handled.
         - If state is already defined such that there are iterations to run until `max_epochs` and no input arguments
           provided, state is kept and used in the function.
@@ -805,9 +802,6 @@ def run(
                 `len(data)`. If `data` is an iterator and `epoch_length` is not set, then it will be automatically
                 determined as the iteration on which data iterator raises `StopIteration`.
                 This argument should not change if run is resuming from a state.
-            max_iters: Number of iterations to run for.
-                `max_iters` and `max_epochs` are mutually exclusive; only one of the two arguments should be provided.
-
         Returns:
             State: output state.
 
@@ -858,6 +852,8 @@ def switch_batch(engine):
 
         if self.state.max_epochs is None or (self._is_done(self.state) and self._internal_run_generator is None):
             # Create new state
+            if max_epochs is None:
+                max_epochs = 1
             if epoch_length is None:
                 if data is None:
                     raise ValueError("epoch_length should be provided if data is None")
@@ -866,22 +862,9 @@ def switch_batch(engine):
                 if epoch_length is not None and epoch_length < 1:
                     raise ValueError("Input data has zero size. Please provide non-empty data")
 
-            if max_iters is None:
-                if max_epochs is None:
-                    max_epochs = 1
-            else:
-                if max_epochs is not None:
-                    raise ValueError(
-                        "Arguments max_iters and max_epochs are mutually exclusive."
-                        "Please provide only max_epochs or max_iters."
-                    )
-                if epoch_length is not None:
-                    max_epochs = math.ceil(max_iters / epoch_length)
-
             self.state.iteration = 0
             self.state.epoch = 0
             self.state.max_epochs = max_epochs
-            self.state.max_iters = max_iters
             self.state.epoch_length = epoch_length
             # Reset generator if previously used
             self._internal_run_generator = None
@@ -1062,18 +1045,12 @@ def _run_once_on_dataset_as_gen(self) -> Generator[State, None, 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 "
@@ -1104,10 +1081,6 @@ 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
@@ -1229,18 +1202,12 @@ 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 "
@@ -1271,10 +1238,6 @@ 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

@@ -443,7 +443,6 @@ class State:
         state.dataloader        # data passed to engine
         state.epoch_length      # optional length of an epoch
         state.max_epochs        # number of epochs to run
-        state.max_iters         # number of iterations to run
         state.batch             # batch passed to `process_function`
         state.output            # output of `process_function` after a single iteration
         state.metrics           # dictionary with defined metrics if any
@@ -470,7 +469,6 @@ def __init__(self, **kwargs: Any) -> None:
         self.epoch = 0
         self.epoch_length: Optional[int] = None
         self.max_epochs: Optional[int] = None
-        self.max_iters: Optional[int] = None
         self.output: Optional[int] = None
         self.batch: Optional[int] = None
         self.metrics: Dict[str, Any] = {}

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):

tests/ignite/engine/test_engine.py

@@ -1026,47 +1026,6 @@ 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

@@ -357,7 +357,7 @@ 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):