code: def prepare_config_and_inputs(self):
      states = floats_tensor(
          (self.batch_size, self.seq_length, self.state_dim)
      )
      actions = floats_tensor(
          (self.batch_size, self.seq_length, self.act_dim)
      )
      rewards = floats_tensor((self.batch_size, self.seq_length, 1))
      returns_to_go = floats_tensor(
          (self.batch_size, self.seq_length, 1)
      )
      timesteps = ids_tensor(
          (self.batch_size, self.seq_length), vocab_size=1000
      )
      attention_mask = random_attention_mask(
          (self.batch_size, self.seq_length)
      )
  
      config = self.get_config()
  
      return (
          config,
          states,
          actions,
          rewards,
          returns_to_go,
          timesteps,
          attention_mask,
      )
  
imports: import inspect
  import unittest
  from transformers import DecisionTransformerConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 2 for calling the DecisionTransformerModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  states,  actions,  rewards,  returns_to_go,  timesteps,  attention_mask