For some reason, the class information is not passed in the sample wrapper

bob/pipelines/wrappers.py

@@ -163,7 +163,7 @@ class SampleWrapper(BaseWrapper, TransformerMixin):
 
         X = SampleBatch(samples)
 
-        self.estimator = self.estimator.fit(X, **kwargs)
+        self.estimator = self.estimator.fit(X, y=y, **kwargs)
         copy_learned_attributes(self.estimator, self)
         return self
 

doc/checkpoint.rst

@@ -40,7 +40,7 @@ transformer.
    ...         print(f"Transforming {len(X)} samples ...")
    ...         return np.array(X) + np.array(sample_specific_offsets)
    ...
-   ...     def fit(self, X):
+   ...     def fit(self, X, y=None):
    ...         print("Fit was called!")
    ...         return self