class_docstr: Approximation of http://ceur-ws.org/Vol-1905/recsys2017_poster3.pdf
  Interactions can be any positive values, but magnitude is ignored. Negative interactions are ignored.
class_docstr_tok: ["Approximation","of","http",":","\/\/ceur-ws.org\/Vol-1905\/recsys2017_poster3.pdf","Interactions","can","be","any","positive","values",",","but","magnitude","is","ignored",".","Negative","interactions","are","ignored","."]
code: def connect_loss_graph(
      self,
      tf_prediction_serial,
      tf_interactions,
      tf_sample_predictions,
      tf_n_items,
      tf_n_sampled_items,
      **kwargs,
  ):
      return self.weighted_margin_rank_batch(
          tf_prediction_serial=tf_prediction_serial,
          tf_interactions=tf_interactions,
          tf_sample_predictions=tf_sample_predictions,
          tf_n_items=tf_n_items,
          tf_n_sampled_items=tf_n_sampled_items,
      )
  
imports: import abc
  import tensorflow
label_desc: Use image node_id 1 for calling the WMRBLossGraph obj's underlying member method code with example usage: obj.connect_loss_graph(tf_prediction_serial, tf_interactions, tf_sample_predictions, tf_n_items, tf_n_sampled_items) and returns: self