code: def compute_log_likelihoods_from_input_dict(
      policy: "Policy",
      batch: Union[SampleBatch, Dict[str, TensorStructType]],
  ):
      """Returns log likelihood for actions in given batch for policy.
  
      Computes likelihoods by passing the observations through the current
      policy's `compute_log_likelihoods()` method
  
      Args:
          batch: The SampleBatch or MultiAgentBatch to calculate action
              log likelihoods from. This batch/batches must contain OBS
              and ACTIONS keys.
  
      Returns:
          The probabilities of the actions in the batch, given the
          observations and the policy.
      """
      num_state_inputs = 0
      for k in batch.keys():
          if k.startswith("state_in_"):
              num_state_inputs += 1
      state_keys = [
          "state_in_{}".format(i) for i in range(num_state_inputs)
      ]
      log_likelihoods: TensorType = policy.compute_log_likelihoods(
          actions=batch[SampleBatch.ACTIONS],
          obs_batch=batch[SampleBatch.OBS],
          state_batches=[batch[k] for k in state_keys],
          prev_action_batch=batch.get(SampleBatch.PREV_ACTIONS),
          prev_reward_batch=batch.get(SampleBatch.PREV_REWARDS),
          actions_normalized=policy.config.get(
              "actions_in_input_normalized", False
          ),
      )
      return log_likelihoods
  
imports: import gymnasium
  import logging
  import numpy
  import re
  from typing import Callable, Dict, List, Mapping, Optional, Tuple, Type, Union, TYPE_CHECKING
  import tree
  import ray.cloudpickle
  from ray.rllib.models.preprocessors import ATARI_OBS_SHAPE
  from ray.rllib.policy.policy import PolicySpec
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.deprecation import Deprecated
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.typing import ActionConnectorDataType, AgentConnectorDataType, AgentConnectorsOutput, PartialAlgorithmConfigDict, PolicyState, TensorStructType, TensorType
  from ray.util import log_once
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 5 for calling a global function with example usage: compute_log_likelihoods_from_input_dict(policy, batch) and returns: log_likelihoods