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Check early stopping metric in the beginning of the training #542

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merged 11 commits into from
Jan 23, 2020
Merged

Check early stopping metric in the beginning of the training #542

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4c635ad
Early stopping fix
kuynzereb Nov 25, 2019
c06bad6
Update trainer.py
williamFalcon Nov 30, 2019
acda2b7
Don't force validation sanity check
kuynzereb Dec 1, 2019
10e76f6
fix tests
kuynzereb Dec 2, 2019
aeb8bbd
Resolved conflicts
kuynzereb Jan 14, 2020
25e1bda
update
kuynzereb Jan 14, 2020
748640b
Added early_stopping check_metrics
kuynzereb Jan 14, 2020
706d84f
Merge branch 'master' into early_stopping_callback_fix
kuynzereb Jan 22, 2020
0f83b1a
Updated docs
kuynzereb Jan 22, 2020
4e35bee
Update docs
kuynzereb Jan 22, 2020
320e4c1
Do not call early stopping when validation is disabled
kuynzereb Jan 22, 2020
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7 changes: 7 additions & 0 deletions pytorch_lightning/trainer/train_loop_mixin.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,6 +113,13 @@ def run_training_epoch(self):
if self.fast_dev_run or should_check_val:
self.run_evaluation(test=self.testing)

if (self.enable_early_stop and
self.callback_metrics.get(self.early_stop_callback.monitor) is None):
raise RuntimeError(f"Early stopping was configured to monitor "
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f"{self.early_stop_callback.monitor} but it is not available"
f" after validation_end. Available metrics are: "
f"{','.join(list(self.callback_metrics.keys()))}")

# when logs should be saved
should_save_log = (batch_nb + 1) % self.log_save_interval == 0 or early_stop_epoch
if should_save_log or self.fast_dev_run:
Expand Down
15 changes: 6 additions & 9 deletions pytorch_lightning/trainer/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -185,8 +185,6 @@ def __init__(self,
# creates a default one if none passed in
self.early_stop_callback = None
self.configure_early_stopping(early_stop_callback, logger)
if self.enable_early_stop:
self.nb_sanity_val_steps = max(1, self.nb_sanity_val_steps)

# configure checkpoint callback
self.checkpoint_callback = checkpoint_callback
Expand Down Expand Up @@ -446,7 +444,6 @@ def run_pretrain_routine(self, model):
# run tiny validation (if validation defined)
# to make sure program won't crash during val
ref_model.on_sanity_check_start()
callback_metrics = {}
if self.get_val_dataloaders() is not None and self.nb_sanity_val_steps > 0:
# init progress bars for validation sanity check
pbar = tqdm.tqdm(desc='Validation sanity check', total=self.nb_sanity_val_steps,
Expand All @@ -464,12 +461,12 @@ def run_pretrain_routine(self, model):
self.main_progress_bar.close()
self.val_progress_bar.close()

if (self.enable_early_stop and
callback_metrics.get(self.early_stop_callback.monitor) is None):
raise RuntimeError(f"Early stopping was configured to monitor "
f"{self.early_stop_callback.monitor} but it is not available "
f"after validation_end. Available metrics are: "
f"{','.join(list(callback_metrics.keys()))}")
if (self.enable_early_stop and
callback_metrics.get(self.early_stop_callback.monitor) is None):
raise RuntimeError(f"Early stopping was configured to monitor "
f"{self.early_stop_callback.monitor} but it is not available "
f"after validation_end. Available metrics are: "
f"{','.join(list(callback_metrics.keys()))}")

# init progress bar
pbar = tqdm.tqdm(leave=True, position=2 * self.process_position,
Expand Down