code: def class_extensions():
      def transform_frame(self, fr):
          """
          GLRM performs A=X*Y during training.  When a new dataset is given, GLRM will perform Anew = Xnew*Y.  When
          predict is called, Xnew*Y is returned.  When transform_frame is called, Xnew is returned instead.
          :return: an H2OFrame that contains Xnew.
          """
          return H2OFrame._expr(
              expr=ExprNode("transform", ASTId(self.key), ASTId(fr.key))
          )._frame(fill_cache=True)
  
label_desc: Use image node_id 1 for calling a global function with example usage: class_extensions() and returns: H2OFrame