class_docstr: TensorFlow Serving binary.
class_docstr_tok: ["TensorFlow","Serving","binary","."]
code: def MakeEnvVars(
      self, model_path: Optional[str] = None
  ) -> Dict[str, str]:
      if model_path is None:
          model_base_path = self._DEFAULT_MODEL_BASE_PATH
      else:
          model_base_path = tf_serving_flavor.parse_model_base_path(
              model_path
          )
      return {
          "MODEL_NAME": self._model_name,
          "MODEL_BASE_PATH": model_base_path,
          "TF_CPP_MAX_VLOG_LEVEL": "3",
      }
  
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 TensorFlowServing obj's underlying member method code with example usage: obj.MakeEnvVars(model_path) and returns: dict