docstr: Converts given data to indexes or to raw data (according to order).
  
  It works for both triples (``type_of='t'``), entities
  (``type_of='e'``), and relations (``type_of='r'``).
  
  Parameters
  ----------
  X: np.array
      Data to be indexed.
  type_of: str
      One of `['e', 't', 'r']` to specify which type of data is to be
      indexed or converted to raw data.
  order: str
      One of `['raw2ind', 'ind2raw']` to specify whether to convert raw
      data to indexes or vice versa.
  
  Returns
  -------
  Y: np.array
      Indexed data or raw data.
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code: def get_indexes(self, X, type_of="t", order="raw2ind"):
      """Converts given data to indexes or to raw data (according to order).
  
      It works for both triples (``type_of='t'``), entities
      (``type_of='e'``), and relations (``type_of='r'``).
  
      Parameters
      ----------
      X: np.array
          Data to be indexed.
      type_of: str
          One of `['e', 't', 'r']` to specify which type of data is to be
          indexed or converted to raw data.
      order: str
          One of `['raw2ind', 'ind2raw']` to specify whether to convert raw
          data to indexes or vice versa.
  
      Returns
      -------
      Y: np.array
          Indexed data or raw data.
      """
      return self.model.get_indexes(X, type_of, order)
  
imports: import numpy
  import tensorflow
  from ampligraph.latent_features.loss_functions import get
  from ampligraph.latent_features.models import ScoringBasedEmbeddingModel
  from ampligraph.latent_features.optimizers import get
  from ampligraph.latent_features.regularizers import get
label_desc: Use image node_id 6 for calling the ScoringModelBase obj's underlying member method code with example usage: obj.get_indexes(X, type_of, order) and returns: self