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 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
 
 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."
 
                 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)
                     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."
                     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)
                     logger.warning(msg)

+                    warnings.warn(msg)

         return (X, y)
 
     def make_progress_graph(self) -> None:
         return (X, y)
 
     def make_progress_graph(self) -> None: