code: def test_prediction(self):
      batch_size = 1
  
      config = TrajectoryTransformerConfig.from_pretrained(
          "CarlCochet/trajectory-transformer-halfcheetah-medium-v2"
      )
      model = TrajectoryTransformerModel.from_pretrained(
          "CarlCochet/trajectory-transformer-halfcheetah-medium-v2",
          config=config,
      )
      model.to(torch_device)
      model.eval()
  
      seq_length = (
          model.config.action_dim + model.config.observation_dim + 1
      )
  
      trajectories = torch.LongTensor(
          [
              [
                  3,
                  19,
                  20,
                  22,
                  9,
                  7,
                  23,
                  10,
                  18,
                  14,
                  13,
                  4,
                  17,
                  11,
                  5,
                  6,
                  15,
                  21,
                  2,
                  8,
                  1,
                  0,
                  12,
                  16,
              ]
          ]
      ).to(torch_device)
      outputs = model(
          trajectories=trajectories,
          output_hidden_states=True,
          output_attentions=True,
          use_cache=True,
          return_dict=True,
      )
  
      output = outputs.logits
  
      expected_shape = torch.Size(
          (batch_size, seq_length, model.config.vocab_size + 1)
      )
      expected_slice = torch.tensor(
          [
              [
                  [-0.7193, -0.2532, -0.0898],
                  [1.9429, 2.0434, 2.3975],
                  [-3.3651, -2.8744, -2.4532],
              ]
          ]
      ).to(torch_device)
      output_slice = output[:, :3, :3]
  
      self.assertEqual(output.shape, expected_shape)
      self.assertTrue(
          torch.allclose(output_slice, expected_slice, atol=1e-4)
      )
  
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 1 for calling the TrajectoryTransformerModelIntegrationTest obj's underlying member method code with example usage: obj.test_prediction() without return types