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>`__.
  
  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. Default: `'BCELoss'`
code: def __init__(self, input_dropout=0.0, loss_name="BCELoss"):
      super(DistMult, self).__init__()
      self.loss_name = loss_name
      self.classifier = DistMultLayer(input_dropout, loss_name)
  
imports: from .....data.data import GraphData
  from ..base import KGCompletionBase
  from .DistMultLayer import DistMultLayer
label_desc: Use image node_id 1 to create a new DistMult object from inherited base classes: KGCompletionBase with example: obj = DistMult(input_dropout, loss_name)