scikit-learn
diff --git a/‎doc/whats_new.rst‎
Lines changed: 1 addition & 2 deletions b/‎doc/whats_new.rst‎
Lines changed: 1 addition & 2 deletions
diff --git a/‎sklearn/pipeline.py‎
Lines changed: 11 additions & 10 deletions b/‎sklearn/pipeline.py‎
Lines changed: 11 additions & 10 deletions
diff --git a/‎sklearn/tests/test_pipeline.py‎
Lines changed: 2 additions & 2 deletions b/‎sklearn/tests/test_pipeline.py‎
Lines changed: 2 additions & 2 deletions
@@ -57,7 +57,7 @@ Miscellaneous
 - Added optional parameter ``verbose`` in functions `pipeline.make_pipeline`
   and `pipeline.make_union` to extend the same functionality as the
   corresponding classes. :issue:`9668` by
-  :user:`Baze Petrushev <petrushev>`.
+  :user:`Baze Petrushev <petrushev>` and :user:`Karan Desai <karandesai-96>`.
 
 
 Bug fixes
@@ -5766,5 +5766,4 @@ David Huard, Dave Morrill, Ed Schofield, Travis Oliphant, Pearu Peterson.
 
 .. _Neeraj Gangwar: http://neerajgangwar.in
 .. _Arthur Mensch: https://amensch.fr
-
 .. _Karan Desai: https://www.github.com/karandesai-96
@@ -18,10 +18,11 @@
 from .base import clone, TransformerMixin
 from .externals.joblib import Parallel, delayed
 from .externals import six
-from .utils.metaestimators import if_delegate_has_method, _BaseComposition
+from .utils.metaestimators import if_delegate_has_method
 from .utils import Bunch
 from .utils.validation import check_memory
 
+from .utils.metaestimators import _BaseComposition
 
 __all__ = ['Pipeline', 'FeatureUnion']
 
@@ -627,16 +628,16 @@ def make_pipeline(*steps, **kwargs):
     return Pipeline(_name_estimators(steps), memory=memory, verbose=verbose)
 
 
-def _fit_one_transformer(trans, X, y, verbose=False, idx=None,
+def _fit_one_transformer(transformer, X, y, verbose=False, idx=None,
                          total_steps=None, name=None):
     # idx, total_steps and name are not required when verbosity is disabled
     step_start_time = time.time()
-    trans = trans.fit(X, y)
+    transformer = transformer.fit(X, y)
     step_time_elapsed = time.time() - step_start_time
     if verbose:
         _pretty_print('[FeatureUnion] (step %d of %d) %s ... %.5fs' %
                       (idx + 1, total_steps, name, step_time_elapsed))
-    return trans
+    return transformer
 
 
 def _transform_one(transformer, weight, X):
@@ -647,22 +648,22 @@ def _transform_one(transformer, weight, X):
     return res * weight
 
 
-def _fit_transform_one(trans, weight, X, y, verbose=False, idx=None,
+def _fit_transform_one(transformer, weight, X, y, verbose=False, idx=None,
                        total_steps=None, name=None, **fit_params):
     # idx, total_steps and name are not required when verbosity is disabled
     step_start_time = time.time()
-    if hasattr(trans, 'fit_transform'):
-        res = trans.fit_transform(X, y, **fit_params)
+    if hasattr(transformer, 'fit_transform'):
+        res = transformer.fit_transform(X, y, **fit_params)
     else:
-        res = trans.fit(X, y, **fit_params).transform(X)
+        res = transformer.fit(X, y, **fit_params).transform(X)
     step_time_elapsed = time.time() - step_start_time
     if verbose:
         _pretty_print('[FeatureUnion] (step %d of %d) %s ... %.5fs' %
                       (idx + 1, total_steps, name, step_time_elapsed))
     # if we have a weight for this transformer, multiply output
     if weight is None:
-        return res, trans
-    return res * weight, trans
+        return res, transformer
+    return res * weight, transformer
 
 
 class FeatureUnion(_BaseComposition, TransformerMixin):
 
@@ -67,12 +67,12 @@ def set_params(self, **params):
 
 
 class NoInvTransf(NoTrans):
-    def transform(self, X, y=None):
+    def transform(self, X):
         return X
 
 
 class Transf(NoInvTransf):
-    def transform(self, X, y=None):
+    def transform(self, X):
         return X
 
     def inverse_transform(self, X):