class_docstr: Runtime parameter.
  
  Currently only supported on KubeflowDagRunner.
  
  For protos, use text type RuntimeParameter, which holds the proto json
  string, e.g., `'{"num_steps": 5}'` for TrainArgs proto.
  
  Attributes:
    name: The name of the runtime parameter.
    default: Default value for runtime params when it's not explicitly
      specified.
    ptype: The type of the runtime parameter.
    description: Description of the usage of the parameter.
docstr: Easily convert RuntimeParameter to str.
  
  This provides a unified way to call str(x) when x can be either str or
  RuntimeParameter. Note: if ptype == Text or None, the serialization will be
  wrapped in double quotes.
  
  Returns:
    The json serialized version of RuntimeParameter.
docstr_tok: ["Easily","convert","RuntimeParameter","to","str",".","This","provides","a","unified","way","to","call","str","(","x",")","when","x","can","be","either","str","or","RuntimeParameter",".","Note",":","if","ptype","==","Text","or","None",",","the","serialization","will","be","wrapped","in","double","quotes",".","Returns",":","The","json","serialized","version","of","RuntimeParameter","."]
code: def __repr__(self):
      """Easily convert RuntimeParameter to str.
  
      This provides a unified way to call str(x) when x can be either str or
      RuntimeParameter. Note: if ptype == Text or None, the serialization will be
      wrapped in double quotes.
  
      Returns:
        The json serialized version of RuntimeParameter.
      """
      return json_utils.dumps(self)
  
imports: from typing import Any, Dict, List, Optional, Type, Union
  from tfx import types
  from tfx.dsl.placeholder import placeholder
  from tfx.utils import json_utils
label_desc: Use image node_id 2 for calling the RuntimeParameter obj's underlying member method code with example usage: obj.__repr__() and returns: json_utils