docstr: Same as get_q_values but using the twin Q net.
  
  This implements the twin Q(s, a).
  
  Args:
      model_out: obs embeddings from the model layers.
          Shape: [BATCH_SIZE, num_outputs].
      actions: Actions to return the Q-values for.
          Shape: [BATCH_SIZE, action_dim].
  
  Returns:
      The q_values based on Q_{twin}(S,A).
      Shape: [BATCH_SIZE].
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code: def get_twin_q_values(
      self, model_out: TensorType, actions: TensorType
  ) -> TensorType:
      """Same as get_q_values but using the twin Q net.
  
      This implements the twin Q(s, a).
  
      Args:
          model_out: obs embeddings from the model layers.
              Shape: [BATCH_SIZE, num_outputs].
          actions: Actions to return the Q-values for.
              Shape: [BATCH_SIZE, action_dim].
  
      Returns:
          The q_values based on Q_{twin}(S,A).
          Shape: [BATCH_SIZE].
      """
      return self._get_q_value(model_out, actions, self.twin_q_model)
  
imports: from typing import Dict, List, Union
  import gymnasium
  import numpy
  from ray.rllib.models.torch.misc import SlimFC
  from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
  from ray.rllib.models.utils import get_activation_fn
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.typing import ModelConfigDict, TensorType
label_desc: Use image node_id 6 for calling the CRRModel obj's underlying member method code with example usage: obj.get_twin_q_values(model_out, actions) and returns: self