class_docstr: TF version of ModelV2, which should contain a tf keras Model.
  
  Note that this class by itself is not a valid model unless you
  implement forward() in a subclass.
class_docstr_tok: ["TF","version","of","ModelV2",",","which","should","contain","a","tf","keras","Model",".","Note","that","this","class","by","itself","is","not","a","valid","model","unless","you","implement","forward","(",")","in","a","subclass","."]
docstr: Return the list of update ops for this model.
  
  For example, this should include any BatchNorm update ops.
docstr_tok: ["Return","the","list","of","update","ops","for","this","model",".","For","example",",","this","should","include","any","BatchNorm","update","ops","."]
code: def update_ops(self) -> List[TensorType]:
      """Return the list of update ops for this model.
  
      For example, this should include any BatchNorm update ops."""
      return []
  
file_path: ray/rllib/models/tf/tf_modelv2.py
imports: import contextlib
  import gymnasium
  import re
  from typing import Dict, List, Union
  from ray.util import log_once
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.utils.annotations import override, PublicAPI
  from ray.rllib.utils.deprecation import deprecation_warning
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.typing import ModelConfigDict, TensorType
label_desc: Use image node_id 3 for calling the TFModelV2 obj's underlying member method code with example usage: obj.update_ops() and returns: list