code: def value_function(self):
      assert self._features is not None, "must call forward() first"
      return torch.reshape(self.value_branch(self._features), [-1])
  
file_path: ray/python/ray/rllib/examples/models/rnn_model.py
imports: import numpy
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.preprocessors import get_preprocessor
  from ray.rllib.models.tf.recurrent_net import RecurrentNetwork
  from ray.rllib.models.torch.recurrent_net import RecurrentNetwork
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
label_desc: Use image node_id 3 for calling the TorchRNNModel obj's underlying member method code with example usage: obj.value_function() and returns: torch