code: def test_step_types_dtype_mismatch_eps(eps_data):
      with pytest.raises(
          ValueError, match="step_types has dtype float32"
      ):
          eps_data["step_types"] = eps_data["step_types"].astype(
              np.float32
          )
          t = EpisodeBatch(**eps_data)
          del t
  
imports: import akro
  import gym.spaces
  import numpy
  import pytest
  from garage import EnvSpec, EnvStep, EpisodeBatch, StepType, TimeStep, TimeStepBatch
label_desc: Use image node_id 18 for calling a global function with example usage: test_step_types_dtype_mismatch_eps(eps_data) without return types