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Fixed step variable sent to loggers to keep it consistent with trainer.global_step #13397

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Fixed step variable sent to loggers to keep it consistent with trainer.global_step #13397

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c8ef4c6
Fixed the bug by changing step variable to trainer.global_step
manangoel99 Jun 24, 2022
8478ca6
Updated tests according to new behaviour of the step argument and upd…
manangoel99 Jun 24, 2022
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2 changes: 1 addition & 1 deletion src/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,7 +99,7 @@ def log_metrics(self, metrics: _OUT_DICT, step: Optional[int] = None) -> None:
if step is None:
# added metrics for convenience
scalar_metrics.setdefault("epoch", self.trainer.current_epoch)
step = self.trainer.fit_loop.epoch_loop._batches_that_stepped
step = self.trainer.global_step - 1
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@rohitgr7 rohitgr7 Jun 24, 2022

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this isn't BC if multiple optimizers are used.
similar issue: #12274

we need to come up with a better solution.


# log actual metrics
for logger in self.trainer.loggers:
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4 changes: 2 additions & 2 deletions tests/tests_pytorch/loggers/test_all.py
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Expand Up @@ -144,14 +144,14 @@ def log_metrics(self, metrics, step):
expected = [
(0, ["epoch", "train_some_val"]),
(0, ["early_stop_on", "epoch", "val_loss"]),
(1, ["epoch", "test_loss"]),
(0, ["epoch", "test_loss"]),
]
assert log_metric_names == expected
else:
expected = [
(0, ["epoch", "train_some_val"]),
(0, ["early_stop_on", "epoch", "val_loss"]),
(1, ["epoch", "test_loss"]),
(0, ["epoch", "test_loss"]),
]
assert log_metric_names == expected

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