code: def fit(self, x, y=None):
      self.encoder.fit(x)
      return self
  
imports: from io import BytesIO
  import os
  import requests
  from zipfile import ZipFile
  import numpy
  import scipy.sparse
  from sklearn.base import TransformerMixin
  from sklearn.feature_extraction.text import CountVectorizer
  from sklearn.pipeline import Pipeline, FeatureUnion
  from sklearn.preprocessing import LabelBinarizer
  from lightfm import datasets
label_desc: Use image node_id 2 for calling the PipelineLabelBinarizer obj's underlying member method code with example usage: obj.fit(x, y) and returns: self