class_docstr: Translating Embeddings (TransE) scoring layer.
  
  The model as described in :cite:`bordes2013translating`.
  
  The scoring function of TransE computes a similarity between the embedding of the subject
  :math:`\mathbf{e}_{sub}` translated by the embedding of the predicate :math:`\mathbf{e}_{pred}`,
  and the embedding of the object :math:`\mathbf{e}_{obj}`,
  using the :math:`L_1` or :math:`L_2` norm :math:`||\cdot||` (default: :math:`L_1`):
  
  .. math::
      f_{TransE}=-||\mathbf{e}_{sub} + \mathbf{e}_{pred} - \mathbf{e}_{obj}||
  
  Such scoring function is then used on positive and negative triples :math:`t^+, t^-` in the loss function.
code: def get_config(self):
      config = super(TransE, self).get_config()
      return config
  
file_path: AmpliGraph/ampligraph/latent_features/layers/scoring/TransE.py
imports: import tensorflow
  from .AbstractScoringLayer import register_layer, AbstractScoringLayer
label_desc: Use image node_id 1 for calling the TransE obj's underlying member method code with example usage: obj.get_config() and returns: config