code: def init_encoders(self, config=DataConfig()):
          
          self.log('info', 'Initializing the encoders ...')
  
          # create the integer encoder and fit it to our corpus' vocab
          self.ie = LabelEncoder()
          self.ie_vocab = self.ie.fit_transform(self.vocab_list)
  
          self.pad_u_index = self.ie.transform([self.pad_u])[0]
  
          # create the OHE encoder and fit it to our corpus' vocab
          self.ohe = OneHotEncoder(sparse=False)
          self.ohe_vocab = self.ohe.fit_transform(self.ie_vocab.reshape(len(self.ie_vocab), 1))
  
          return
docs: Initialize the integer encoder and the one-hot encoder, fitting them to the vocabulary
          of the corpus.
  
          NB:
          From here on out,
              - 'ie' stands for 'integer encoded', and
              - 'ohe' stands for 'one-hot encoded'