class_docstr: Hyperbolic rotation model using 2 x 2 givens rotations.
class_docstr_tok: ["Hyperbolic","rotation","model","using","2","x","2","givens","rotations","."]
code: def __init__(self, sizes, args):
      super(RotH, self).__init__(sizes, args)
      self.rot = tf.keras.layers.Embedding(
          input_dim=sizes[1],
          output_dim=self.rank,
          embeddings_initializer=self.initializer,
          embeddings_regularizer=self.rel_regularizer,
          name="rotation_weights",
      )
      self.rot_trans = tf.keras.layers.Embedding(
          input_dim=sizes[1],
          output_dim=self.rank,
          embeddings_initializer=self.initializer,
          embeddings_regularizer=self.rel_regularizer,
          name="translation_weights",
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from kg_hyp_emb.models.base import KGModel
  from kg_hyp_emb.utils import euclidean
  from kg_hyp_emb.utils import hyperbolic
  import numpy
  import tensorflow
label_desc: Use image node_id 1 to create a new RotH object from inherited base classes: BaseH with example: obj = RotH(sizes, args)