'Transform data X according to the fitted model.
.. versionchanged:: 0.18
*doc_topic_distr* is now normalized
Parameters
X : array-like or sparse matrix, shape=(n_samples, n_features)
Document word matrix.
Returns
doc_topic_distr : shape=(n_samples, n_components)
Document topic distribution for X.'

def transform(self, X):

    doc_topic_distr = self._unnormalized_transform(X)
    doc_topic_distr /= doc_topic_distr.sum(axis=1)[:, np.newaxis]
    return doc_topic_distr
