Try something else

Author: Guillaume Lemaitre

imblearn/base.py

@@ -260,9 +260,6 @@ def fit(self, X, y):
 
         super(BaseBinarySampler, self).fit(X, y)
 
-        if np.size(np.unique(y)) == 1:
-            warnings.warn('Hello')
-
         # Check that the target type is binary
         if not type_of_target(y) == 'binary':
             warnings.warn('The target type should be binary.')
@@ -298,9 +295,6 @@ def fit(self, X, y):
 
         super(BaseMulticlassSampler, self).fit(X, y)
 
-        if np.size(np.unique(y)) == 1:
-            warnings.warn('Hello')
-
         # Check that the target type is either binary or multiclass
         if not (type_of_target(y) == 'binary' or
                 type_of_target(y) == 'multiclass'):