class_docstr: Specific class for knowledge graph completion task.
  
  DistMult from paper `Embedding entities and relations for learning and
  inference in knowledge bases <https://arxiv.org/pdf/1412.6575.pdf>`__.
  
  .. math::
      f(s, r, o) & = e_s^T R_r e_o
  
  Parameters
  ----------
  input_dropout: float
      Dropout for node_emb and rel_emb. Default: 0.0
  
  loss_name: str
      The loss type selected fot the KG completion task.
code: def __init__(self, input_dropout=0.0, loss_name="BCELoss"):
      super(DistMultLayer, self).__init__()
      self.inp_drop = nn.Dropout(input_dropout)
      self.loss_name = loss_name
  
imports: import torch
  from torch import nn
  from ..base import KGCompletionLayerBase
label_desc: Use image node_id 1 to create a new DistMultLayer object from inherited base classes: KGCompletionLayerBase with example: obj = DistMultLayer(input_dropout, loss_name)