code: def __init__(
      self,
      model,
      input_record,
      name="margin_rank_loss",
      margin=0.1,
      average_loss=False,
      **kwargs,
  ):
      super().__init__(model, name, input_record, **kwargs)
      assert (
          margin >= 0
      ), "For hinge loss, margin should be no less than 0"
      self._margin = margin
      self._average_loss = average_loss
      assert schema.is_schema_subset(
          schema.Struct(
              ("pos_prediction", schema.Scalar()),
              ("neg_prediction", schema.List(np.float32)),
          ),
          input_record,
      )
      self.tags.update([Tags.EXCLUDE_FROM_PREDICTION])
      self.output_schema = schema.Scalar(
          np.float32, self.get_next_blob_reference("output")
      )
  
imports: from caffe2.python import schema, core
  from caffe2.python.layers.layers import ModelLayer
  from caffe2.python.layers.tags import Tags
  import numpy
label_desc: Use image node_id 1 to create a new MarginRankLoss object from inherited base classes: ModelLayer with example: obj = MarginRankLoss(model, input_record, name, margin, average_loss)