code: def prepare_config_and_inputs(self):
      trajectories = torch.LongTensor(
          [
              np.random.permutation(self.seq_length)
              for _ in range(self.batch_size)
          ]
      ).to(torch_device)
      attention_mask = random_attention_mask(
          (self.batch_size, self.seq_length)
      ).to(torch_device)
      targets = torch.LongTensor(
          [
              np.random.permutation(self.seq_length)
              for _ in range(self.batch_size)
          ]
      ).to(torch_device)
  
      config = self.get_config()
      return config, trajectories, attention_mask, targets
  
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 2 for calling the TrajectoryTransformerModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  trajectories,  attention_mask,  targets