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

This reverts commit 307ac11.

ignite/engine/engine.py

@@ -1,6 +1,5 @@
 import functools
 import logging
-import math
 import time
 import warnings
 import weakref
@@ -508,7 +507,7 @@ def load_state_dict(self, state_dict: Mapping) -> None:
         `seed`. If `engine.state_dict_user_keys` contains keys, they should be also present in the state dictionary.
         Iteration and epoch values are 0-based: the first iteration or epoch is zero.
 
-        This method does not remove any custom attributes added by user.
+        This method does not remove any custom attributs added by user.
 
         Args:
             state_dict: a dict with parameters
@@ -553,14 +552,7 @@ 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 state.iteration == state.epoch_length * state.max_epochs  # type: ignore[operator]
 
     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
@@ -602,15 +594,14 @@ def run(
         self,
         data: Optional[Iterable] = None,
         max_epochs: Optional[int] = None,
-        max_iters: Optional[int] = None,
         epoch_length: Optional[int] = None,
         seed: 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`, `seed`, if provided.
+        - At the first call, new state is defined by `max_epochs`, `epoch_length`, `seed`, 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.
@@ -628,8 +619,6 @@ 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.
             seed: Deprecated argument. Please, use `torch.manual_seed` or :meth:`~ignite.utils.manual_seed`.
 
         Returns:
@@ -688,6 +677,8 @@ def switch_batch(engine):
 
         if self.state.max_epochs is None or self._is_done(self.state):
             # 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")
@@ -696,22 +687,9 @@ 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
             self.logger.info(f"Engine run starting with max_epochs={max_epochs}.")
         else:
@@ -765,7 +743,7 @@ def _internal_run(self) -> State:
         try:
             start_time = time.time()
             self._fire_event(Events.STARTED)
-            while not self._is_done(self.state) and not self.should_terminate:
+            while self.state.epoch < self.state.max_epochs and not self.should_terminate:  # type: ignore[operator]
                 self.state.epoch += 1
                 self._fire_event(Events.EPOCH_STARTED)
 
@@ -835,8 +813,6 @@ def _run_once_on_dataset(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
@@ -876,10 +852,6 @@ def _run_once_on_dataset(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
-                    break
-
         except Exception as e:
             self.logger.error(f"Current run is terminating due to exception: {e}")
             self._handle_exception(e)

ignite/engine/events.py

@@ -375,7 +375,6 @@ 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
@@ -402,7 +401,6 @@ def __init__(self, **kwargs: Any) -> None:
         self.epoch = 0
         self.epoch_length = None  # type: Optional[int]
         self.max_epochs = None  # type: Optional[int]
-        self.max_iters = None  # type: Optional[int]
         self.output = None  # type: Optional[int]
         self.batch = None  # type: Optional[int]
         self.metrics = {}  # type: Dict[str, Any]

tests/ignite/engine/test_engine.py

@@ -894,109 +894,6 @@ def switch_dataloader():
     trainer.run(data1, max_epochs=10)
 
 
-def test_run_with_max_iters():
-    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():
-    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():
-    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 = 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():
-    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():
-    torch.cuda.empty_cache()
-
-    engine = Engine(lambda e, b: None)
-
-    def _test():
-        mem_consumption = []
-
-        def dataloader():
-            for _ in range(4):
-                mem_consumption.append(torch.cuda.memory_allocated())
-                batch = torch.randn(10).cuda()
-                mem_consumption.append(torch.cuda.memory_allocated())
-                yield batch
-
-        engine.run(dataloader(), max_epochs=2, epoch_length=2)
-        return mem_consumption
-
-    mem_consumption1 = _test()
-    # mem_consumption should look like [0, 512, 512, 512, 512, 512, 512, 512]
-    assert len(set(mem_consumption1[1:])) == 1
-
-    mem_consumption2 = _test()
-    assert len(set(mem_consumption2[1:])) == 1
-
-    assert mem_consumption1 == mem_consumption2
-
-
-@pytest.mark.skipif(torch.cuda.device_count() < 1, reason="Skip if no GPU")
-def test_output_is_released_before_new_one_is_assigned_on_cuda():
-    torch.cuda.empty_cache()
-
-    def _test():
-        mem_consumption = []
-
-        def update_fn(engine, batch):
-            mem_consumption.append(torch.cuda.memory_allocated())
-            output = torch.rand(10).cuda()
-            mem_consumption.append(torch.cuda.memory_allocated())
-            return output
-
-        engine = Engine(update_fn)
-        engine.run([0, 1], max_epochs=2)
-
-        return mem_consumption
-
-    mem_consumption1 = _test()
-    # mem_consumption ~ [0, 512, 0, 512, 0, 512, 0, 512]
-    assert len(set(mem_consumption1)) == 2
-
-    mem_consumption2 = _test()
-    assert len(set(mem_consumption2)) == 2
-
-    assert mem_consumption1 == mem_consumption2
-
-
 def test_engine_no_data_asserts():
     trainer = Engine(lambda e, b: None)