code: def forward(
      self,
      input_dict: Dict[str, TensorType],
      state: List[TensorType],
      seq_lens: TensorType,
  ) -> (TensorType, List[TensorType]):
      # True No-op forward method.
      # TODO: Support image observation inputs
      return input_dict["obs"], state
  
imports: from typing import Dict, List
  import gymnasium
  import numpy
  from gymnasium.spaces import Box, Discrete
  from ray.rllib import SampleBatch
  from ray.rllib.models import ModelV2
  from ray.rllib.models.torch.mingpt import GPT, GPTConfig
  from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
  from ray.rllib.policy.view_requirement import ViewRequirement
  from ray.rllib.utils import override
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.typing import ModelConfigDict, TensorType
label_desc: Use image node_id 10 for calling the DTTorchModel obj's underlying member method code with example usage: obj.forward(input_dict, state, seq_lens) and returns: input_dict,  state