class_docstr: DistMult scoring layer.
  
  The model as described in :cite:`yang2014embedding`.
  
  The bilinear diagonal DistMult model uses the trilinear dot product as scoring function:
  
  .. math::
      f_{DistMult}=\langle \mathbf{r}_p, \mathbf{e}_s, \mathbf{e}_o \rangle
  
  where :math:`\mathbf{e}_{s}` is the embedding of the subject, :math:`\mathbf{r}_{p}` the embedding
  of the predicate and :math:`\mathbf{e}_{o}` the embedding of the object.
code: def get_config(self):
      config = super(DistMult, self).get_config()
      return config
  
file_path: AmpliGraph/ampligraph/latent_features/layers/scoring/DistMult.py
imports: import tensorflow
  from .AbstractScoringLayer import register_layer, AbstractScoringLayer
label_desc: Use image node_id 1 for calling the DistMult obj's underlying member method code with example usage: obj.get_config() and returns: config