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'

def init_encoders(self, config=DataConfig()):
        """
        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'
        """
        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