code: def create_and_check_model(self, config, input_dict):
      model = TrajectoryTransformerModel(config=config)
      model.to(torch_device)
      model.eval()
  
      result = model(
          trajectories=input_dict["trajectories"],
          attention_mask=input_dict["attention_mask"],
      )
      result = model(
          trajectories=input_dict["trajectories"],
          output_hidden_states=True,
          output_attentions=True,
          use_cache=True,
          return_dict=True,
      )
  
      self.parent.assertEqual(
          result.hidden_states[-1].shape,
          (self.batch_size, self.seq_length, self.n_embd),
      )
  
imports: import inspect
  import unittest
  import numpy
  from transformers import TrajectoryTransformerConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, random_attention_mask
label_desc: Use image node_id 4 for calling the TrajectoryTransformerModelTester obj's underlying member method code with example usage: obj.create_and_check_model(config, input_dict) without return types