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Removed state.restart method #1385

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Merged
merged 1 commit into from
Oct 14, 2020
Merged

Removed state.restart method #1385

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7 changes: 3 additions & 4 deletions ignite/engine/engine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -639,16 +639,15 @@ def run(
def switch_batch(engine):
engine.state.batch = preprocess_batch(engine.state.batch)

Restart the training from the beginning. User can reset `max_epochs = None` or either call
`trainer.state.restart()`:
Restart the training from the beginning. User can reset `max_epochs = None`:

.. code-block:: python

# ...
trainer.run(train_loader, max_epochs=5)

# Reset model weights etc. and restart the training
trainer.state.restart() # equivalent to trainer.state.max_epochs = None
trainer.state.max_epochs = None
trainer.run(train_loader, max_epochs=2)

"""
Expand All @@ -667,7 +666,7 @@ def switch_batch(engine):
if max_epochs < self.state.epoch:
raise ValueError(
"Argument max_epochs should be larger than the start epoch "
"defined in the state: {} vs {}. Please, call state.restart() "
"defined in the state: {} vs {}. Please, set engine.state.max_epochs = None "
"before calling engine.run() in order to restart the training from the beginning.".format(
max_epochs, self.state.epoch
)
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3 changes: 0 additions & 3 deletions ignite/engine/events.py
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Expand Up @@ -396,9 +396,6 @@ def get_event_attrib_value(self, event_name: Union[CallableEventWithFilter, Enum
raise RuntimeError("Unknown event name '{}'".format(event_name))
return getattr(self, State.event_to_attr[event_name])

def restart(self) -> None:
self.max_epochs = None

def __repr__(self) -> str:
s = "State:\n"
for attr, value in self.__dict__.items():
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4 changes: 2 additions & 2 deletions tests/ignite/engine/test_engine_state_dict.py
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Expand Up @@ -276,9 +276,9 @@ def test_restart_training():
with pytest.raises(
ValueError,
match=r"Argument max_epochs should be larger than the start epoch defined in the state: 2 vs 5. "
r"Please, call state.restart\(\) "
r"Please, .+ "
r"before calling engine.run\(\) in order to restart the training from the beginning.",
):
state = engine.run(data, max_epochs=2)
state.restart()
state.max_epochs = None
engine.run(data, max_epochs=2)