code: def test_random_maker_ops_no_seed():
      # Testing the initialization when seed=None
      # Since internal states randomly generated,
      # we just check the output classes
      z = function(inputs=[], outputs=[RandomState()])()
      aes_res = z[0]
      assert isinstance(aes_res, np.random.RandomState)
  
      z = function(inputs=[], outputs=[default_rng()])()
      aes_res = z[0]
      assert isinstance(aes_res, np.random.Generator)
  
imports: import numpy
  import pytest
  import pytensor.tensor
  from pytensor import config, function
  from pytensor.gradient import NullTypeGradError, grad
  from pytensor.graph.replace import vectorize_node
  from pytensor.raise_op import Assert
  from pytensor.tensor.math import eq
  from pytensor.tensor.random import normal
  from pytensor.tensor.random.op import RandomState, RandomVariable, default_rng
  from pytensor.tensor.shape import specify_shape
  from pytensor.tensor.type import all_dtypes, iscalar, tensor
label_desc: Use image node_id 7 for calling a global function with example usage: test_random_maker_ops_no_seed() without return types