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.
code: def __init__(
      self,
      name: str,
      ptype: Optional[Type] = None,  # pylint: disable=g-bare-generic
      default: Optional[Union[int, float, str]] = None,
      description: Optional[str] = None,
  ):
      if ptype and ptype not in [int, float, str]:
          raise RuntimeError(
              "Only str and scalar runtime parameters are supported"
          )
      if (default and ptype) and not isinstance(default, ptype):
          raise TypeError(
              "Default value must be consistent with specified ptype"
          )
      self.name = name
      self.default = default
      self.ptype = ptype
      self.description = description
  
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 1 to create a new RuntimeParameter object from inherited base classes: json_utils with example: obj = RuntimeParameter(name, ptype, default, description)