PairFeatureExtractor.fit_transform() throws exception

[delip]

I am working through the example in the "highered dataset" notebook, and I'm particularly interested in token-level features. But when I run this part of the code:

real = [
    lambda i, j, s1, s2: 1.0,
    lambda i, j, s1, s2: 1.0 if s1[i] == s2[j] else 0.0,
    lambda i, j, s1, s2: 1.0 if s1[i] == s2[j] and len(s1[i]) >= 6 else 0.0,
    lambda i, j, s1, s2: 1.0 if s1[i].isdigit() and s2[j].isdigit() and s1[i] == s2[j] else 0.0,
    lambda i, j, s1, s2: 1.0 if s1[i].isalpha() and s2[j].isalpha() and s1[i] == s2[j] else 0.0,
    lambda i, j, s1, s2: 1.0 if not s1[i].isalpha() and not s2[j].isalpha() else 0.0
]
# Other ideas are:
#  to look up whether words are dictionary words,
#  longest common subsequence,
#  standard edit distance
feature_extractor = PairFeatureExtractor(real=real)
X_extracted = feature_extractor.fit_transform(tokX)

I get the following exception:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-10-04ddbdf4798d> in <module>()
      1 feature_extractor = PairFeatureExtractor(real=real)
----> 2 X_extracted = feature_extractor.fit_transform(tokX)

/home/delip/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pyhacrf/feature_extraction.pyc in fit_transform(self, raw_X, y)
    108             Feature matrix list, for use with estimators or further transformers.
    109         """
--> 110         return self.transform(raw_X)
    111 
    112     def transform(self, raw_X, y=None):

/home/delip/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pyhacrf/feature_extraction.pyc in transform(self, raw_X, y)
    124             Feature matrix list, for use with estimators or further transformers.
    125         """
--> 126         return [self._extract_features(sequence1, sequence2) for sequence1, sequence2 in raw_X]
    127 
    128     def _extract_features(self, sequence1, sequence2):

/home/delip/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pyhacrf/feature_extraction.pyc in _extract_features(self, sequence1, sequence2)
    138 
    139         for k, feature_function in enumerate(self._binary_features):
--> 140             feature_array[..., k] = feature_function(array1, array2)
    141 
    142         if self._sparse_features:

TypeError: <lambda>() takes exactly 4 arguments (2 given)

Any suggestions on what I can do or I should be doing? I'm executing the python notebook code as is.