class_docstr: Base class for serving binaries.
class_docstr_tok: ["Base","class","for","serving","binaries","."]
docstr: Make parameters for docker `client.containers.run`.
  
  Only applies to docker compatible serving binaries.
  
  Args:
    *args: List of unresolved variables to configure docker run parameters.
  
  Returns:
    A dictionary of docker run parameters.
docstr_tok: ["Make","parameters","for","docker","`","client.containers.run","`",".","Only","applies","to","docker","compatible","serving","binaries",".","Args",":","*","args",":","List","of","unresolved","variables","to","configure","docker","run","parameters",".","Returns",":","A","dictionary","of","docker","run","parameters","."]
code: def MakeDockerRunParams(self, *args: Any) -> Dict[str, str]:
      """Make parameters for docker `client.containers.run`.
  
      Only applies to docker compatible serving binaries.
  
      Args:
        *args: List of unresolved variables to configure docker run parameters.
  
      Returns:
        A dictionary of docker run parameters.
      """
      raise NotImplementedError(
          "{} is not docker compatible.".format(type(self).__name__)
      )
  
imports: import abc
  import os
  from typing import Any, Dict, List, Optional
  from docker import types
  from tfx.components.infra_validator.model_server_clients import base_client
  from tfx.components.infra_validator.model_server_clients import tensorflow_serving_client
  from tfx.proto import infra_validator_pb2
  from tfx.utils.model_paths import tf_serving_flavor
label_desc: Use image node_id 4 for calling the ServingBinary obj's underlying member method code with example usage: obj.MakeDockerRunParams() without return types