Start using warnings from stdlib.

[python_utils.git] / ml / model_trainer.py

diff --git a/ml/model_trainer.py b/ml/model_trainer.py
index acd721868a2a9e04de0da364b8d37dcc268b4fee..79ce7062b5b4a05616cddcf7b3d35d59cfbef007 100644 (file)
--- a/ml/model_trainer.py
+++ b/ml/model_trainer.py
@@ -12,6 +12,7 @@ import random
 import sys
 from types import SimpleNamespace
 from typing import Any, List, NamedTuple, Optional, Set, Tuple
+import warnings
 
 import numpy as np
 from sklearn.model_selection import train_test_split  # type:ignore
@@ -247,13 +248,13 @@ class TrainingBlueprint(ABC):
 
                 if self.spec.delete_bad_inputs:
                     msg = f"WARNING: {filename}: missing features or label; expected {self.spec.feature_count} but saw {len(x)}.  DELETING."
-                    print(msg, file=sys.stderr)
                     logger.warning(msg)
+                    warnings.warn(msg)
                     os.remove(filename)
                 else:
                     msg = f"WARNING: {filename}: missing features or label; expected {self.spec.feature_count} but saw {len(x)}.  Skipping."
-                    print(msg, file=sys.stderr)
                     logger.warning(msg)
+                    warnings.warn(msg)
         return (X, y)
 
     def make_progress_graph(self) -> None: