code: def build_transformer(self):
      # build the model
      gpt_config = GPTConfig(
          block_size=self.block_size,
          n_layer=self.model_config["num_layers"],
          n_head=self.model_config["num_heads"],
          n_embed=self.embed_dim,
          embed_pdrop=self.model_config["embed_pdrop"],
          resid_pdrop=self.model_config["resid_pdrop"],
          attn_pdrop=self.model_config["attn_pdrop"],
      )
      gpt = GPT(gpt_config)
      return gpt
  
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 2 for calling the DTTorchModel obj's underlying member method code with example usage: obj.build_transformer() and returns: gpt