Yield stack trace information in resilient mode model_selection warnings

sklearn/exceptions.py

@@ -138,7 +138,10 @@ class FitFailedWarning(RuntimeWarning):
     ...     print(repr(w[-1].message))
     FitFailedWarning('Estimator fit failed. The score on this train-test
     partition for these parameters will be set to 0.000000.
-    Details: \\nValueError: Penalty term must be positive; got (C=-2)\\n'...)
+    Details:
+    \\nTraceback (most recent call last):...\\nValueError:
+    Penalty term must be positive; got (C=-2)\\n')
+
 
     .. versionchanged:: 0.18
        Moved from sklearn.cross_validation.

sklearn/model_selection/_validation.py

@@ -13,7 +13,7 @@
 import warnings
 import numbers
 import time
-from traceback import format_exception_only
+from traceback import format_exc
 from contextlib import suppress
 
 import numpy as np
@@ -532,7 +532,7 @@ def _fit_and_score(estimator, X, y, scorer, train, test, verbose,
             warnings.warn("Estimator fit failed. The score on this train-test"
                           " partition for these parameters will be set to %f. "
                           "Details: \n%s" %
-                          (error_score, format_exception_only(type(e), e)[0]),
+                          (error_score, format_exc()),
                           FitFailedWarning)
         else:
             raise ValueError("error_score must be the string 'raise' or a"

sklearn/model_selection/tests/test_validation.py

@@ -1637,8 +1637,22 @@ def test_fit_and_score_failing():
                        "partition for these parameters will be set to %f. "
                        "Details: \n%s" % (fit_and_score_kwargs['error_score'],
                                           error_message))
+
+    def test_warn_no_trace(msg):
+        split = msg.splitlines()  # note: handles more than '\n'
+        mtb = split[0] + '\n' + split[-1]
+        return warning_message in mtb
     # check if the same warning is triggered
-    assert_warns_message(FitFailedWarning, warning_message, _fit_and_score,
+    assert_warns_message(FitFailedWarning, test_warn_no_trace, _fit_and_score,
+                         *fit_and_score_args, **fit_and_score_kwargs)
+
+    def test_warn_trace(msg):
+        assert(msg.find('Traceback (most recent call last):\n') > -1)
+        split = msg.splitlines()  # note: handles more than '\n'
+        mtb = split[0] + '\n' + split[-1]
+        return warning_message in mtb
+    # check traceback is included
+    assert_warns_message(FitFailedWarning, test_warn_trace, _fit_and_score,
                          *fit_and_score_args, **fit_and_score_kwargs)
 
     fit_and_score_kwargs = {'error_score': 'raise'}