class_docstr: Example of a TorchModelV2 using batch normalization.
code: def value_function(self):
      assert self._hidden_out is not None, "must call forward first!"
      return torch.reshape(self._value_branch(self._hidden_out), [-1])
  
imports: import numpy
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.misc import normc_initializer
  from ray.rllib.models.tf.tf_modelv2 import TFModelV2
  from ray.rllib.models.torch.misc import SlimFC, normc_initializer
  from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
  from ray.rllib.policy.sample_batch import SampleBatch
  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 TorchBatchNormModel obj's underlying member method code with example usage: obj.value_function() and returns: torch