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fix: clean up logging (#587)

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* fix: don't log all-nan metrics

* fix: typo in logging

* chore: ruff

---------

Co-authored-by: Rafi Brent <rafi.brent@gmail.com>
This commit is contained in:
Rafael Brent
2025-11-10 14:23:07 -08:00
committed by GitHub
parent 2ee287a1d5
commit 36f668b5ae
1 changed files with 5 additions and 2 deletions
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7
models/rf3/src/rf3/callbacks/metrics_logging.py
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@@ -121,7 +121,7 @@ class StoreValidationMetricsInDFCallback(BaseCallback):
) )
ranked_logger.info( ranked_logger.info(
f"Validation Progress: {100 * batch_idx / num_batches:.0f}% for {dataset_name}" f"Validation Progress: {100 * (batch_idx + 1) / num_batches:.0f}% for {dataset_name}"
) )
def on_validation_epoch_end(self): def on_validation_epoch_end(self):
@@ -292,7 +292,10 @@ class LogAF3ValidationMetricsCallback(BaseCallback):
# +----------------- Other metrics -----------------+ # +----------------- Other metrics -----------------+
remaining_cols = list(set(dataset_df.columns) - set(by_type_lddt_cols)) remaining_cols = list(set(dataset_df.columns) - set(by_type_lddt_cols))
remaining_df = dataset_df[remaining_cols].copy() remaining_df = dataset_df[remaining_cols].copy()
remaining_df = remaining_df.dropna(how="all") remaining_df = remaining_df.dropna(how="all", axis=0)
remaining_df = remaining_df.dropna(
how="all", axis=1
) # If a Metric is all NaNs for this dataset, drop it
numeric_cols = remaining_df.select_dtypes(include="number").columns numeric_cols = remaining_df.select_dtypes(include="number").columns
# Compute means and non-NaN counts for numeric columns # Compute means and non-NaN counts for numeric columns