class_docstr: This loss function returns the root mean square error between the predictions and the true interactions.
  Interactions can be any positive or negative values, and this loss function is sensitive to magnitude.
class_docstr_tok: ["This","loss","function","returns","the","root","mean","square","error","between","the","predictions","and","the","true","interactions",".","Interactions","can","be","any","positive","or","negative","values",",","and","this","loss","function","is","sensitive","to","magnitude","."]
code: def connect_loss_graph(
      self, tf_prediction_serial, tf_interactions_serial, **kwargs
  ):
      return tf.sqrt(
          tf.reduce_mean(
              tf.square(tf_interactions_serial - tf_prediction_serial)
          )
      )
  
imports: import abc
  import tensorflow
label_desc: Use image node_id 1 for calling the RMSELossGraph obj's underlying member method code with example usage: obj.connect_loss_graph(tf_prediction_serial, tf_interactions_serial) and returns: tf