code: def _common_forward(self, batch):
      obs = batch["obs"]
      global_enc = self.encoder(obs["global"])
      policy_in = tf.concat([global_enc, obs["local"]], axis=-1)
      action_logits = self.policy_head(policy_in)
  
      return {SampleBatch.ACTION_DIST_INPUTS: action_logits}
  
imports: import tensorflow
  from typing import Any, Mapping
  from ray.rllib.core.rl_module.rl_module import RLModule, RLModuleConfig
  from ray.rllib.models.tf.tf_distributions import TfCategorical
  from ray.rllib.core.rl_module.marl_module import MultiAgentRLModule, MultiAgentRLModuleConfig
  from ray.rllib.core.rl_module.tf.tf_rl_module import TfRLModule
  from ray.rllib.core.models.specs.typing import SpecType
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.nested_dict import NestedDict
label_desc: Use image node_id 6 for calling the BCTfRLModuleWithSharedGlobalEncoder obj's underlying member method code with example usage: obj._common_forward(batch) and returns: dict