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ObjectDetectionTask: explicit batch size #1928

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Mar 3, 2024
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ObjectDetectionTask: explicit batch size #1928

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2 changes: 0 additions & 2 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -267,8 +267,6 @@ filterwarnings = [
"ignore:Skipping device Apple Paravirtual device that does not support Metal 2.0:UserWarning",

# Unexpected warnings, worth investigating
# Lightning is having trouble inferring the batch size for ChesapeakeCVPRDataModule and CycloneDataModule for some reason
"ignore:Trying to infer the `batch_size` from an ambiguous collection:UserWarning",
# https://github.com/pytest-dev/pytest/issues/11461
"ignore::pytest.PytestUnraisableExceptionWarning",
]
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6 changes: 3 additions & 3 deletions torchgeo/trainers/detection.py
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Expand Up @@ -242,7 +242,7 @@ def training_step(
]
loss_dict = self(x, y)
train_loss: Tensor = sum(loss_dict.values())
self.log_dict(loss_dict)
self.log_dict(loss_dict, batch_size=batch_size)
return train_loss

def validation_step(
Expand All @@ -267,7 +267,7 @@ def validation_step(
# https://github.com/Lightning-AI/torchmetrics/pull/1832#issuecomment-1623890714
metrics.pop("val_classes", None)

self.log_dict(metrics)
self.log_dict(metrics, batch_size=batch_size)

if (
batch_idx < 10
Expand Down Expand Up @@ -321,7 +321,7 @@ def test_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None
# https://github.com/Lightning-AI/torchmetrics/pull/1832#issuecomment-1623890714
metrics.pop("test_classes", None)

self.log_dict(metrics)
self.log_dict(metrics, batch_size=batch_size)

def predict_step(
self, batch: Any, batch_idx: int, dataloader_idx: int = 0
Expand Down
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