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fixed val_loss for early stopping

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William Falcon
2020-04-26 12:27:19 -04:00
parent f3369666e6
commit a258d3d31b
2 changed files with 3 additions and 3 deletions
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docs/source/introduction_guide.rst
+2 -2
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@@ -654,7 +654,7 @@ sample split in the `train_dataloader` method.
def validation_epoch_end(self, outputs):
avg_loss = torch.stack([x['val_loss'] for x in outputs]).mean()
tensorboard_logs = {'val_loss': avg_loss}
return {'avg_val_loss': avg_loss, 'log': tensorboard_logs}
return {'val_loss': avg_loss, 'log': tensorboard_logs}
def val_dataloader(self):
transform=transforms.Compose([transforms.ToTensor(),
@@ -710,7 +710,7 @@ Just like the validation loop, we define exactly the same steps for testing:
def test_epoch_end(self, outputs):
avg_loss = torch.stack([x['val_loss'] for x in outputs]).mean()
tensorboard_logs = {'val_loss': avg_loss}
return {'avg_val_loss': avg_loss, 'log': tensorboard_logs}
return {'val_loss': avg_loss, 'log': tensorboard_logs}
def test_dataloader(self):
transform=transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))])
docs/source/new-project.rst
+1 -1
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@@ -100,7 +100,7 @@ To also add a validation loop add the following functions
def validation_epoch_end(self, outputs):
avg_loss = torch.stack([x['val_loss'] for x in outputs]).mean()
tensorboard_logs = {'val_loss': avg_loss}
return {'avg_val_loss': avg_loss, 'log': tensorboard_logs
return {'val_loss': avg_loss, 'log': tensorboard_logs
def val_dataloader(self):
# TODO: do a real train/val split