class_docstr: Defines an abstract neural network model for use with RLlib.
  
  Custom models should extend either TFModelV2 or TorchModelV2 instead of
  this class directly.
  
  Data flow:
      obs -> forward() -> model_out
          \-> value_function() -> V(s)
class_docstr_tok: ["Defines","an","abstract","neural","network","model","for","use","with","RLlib",".","Custom","models","should","extend","either","TFModelV2","or","TorchModelV2","instead","of","this","class","directly",".","Data","flow",":","obs","-",">","forward","(",")","-",">","model_out","\\-",">","value_function","(",")","-",">","V","(","s",")"]
docstr: Returns a contextmanager for the current forward pass.
docstr_tok: ["Returns","a","contextmanager","for","the","current","forward","pass","."]
code: def context(self) -> contextlib.AbstractContextManager:
      """Returns a contextmanager for the current forward pass."""
      return NullContextManager()
  
imports: from collections import OrderedDict
  import contextlib
  import gymnasium
  from gymnasium.spaces import Space
  import numpy
  from typing import Dict, List, Any, Union
  from ray.rllib.models.preprocessors import get_preprocessor, RepeatedValuesPreprocessor
  from ray.rllib.models.repeated_values import RepeatedValues
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.view_requirement import ViewRequirement
  from ray.rllib.utils import NullContextManager
  from ray.rllib.utils.annotations import DeveloperAPI, PublicAPI
  from ray.rllib.utils.deprecation import Deprecated
  from ray.rllib.utils.framework import try_import_tf, try_import_torch, TensorType
  from ray.rllib.utils.spaces.repeated import Repeated
  from ray.rllib.utils.typing import ModelConfigDict, ModelInputDict, TensorStructType
label_desc: Use image node_id 10 for calling the ModelV2 obj's underlying member method code with example usage: obj.context() and returns: NullContextManager