code: def test_random_maker_op(seed, maker_op, numpy_res):
      seed = pt.as_tensor_variable(seed)
      z = function(inputs=[], outputs=[maker_op(seed)])()
      aes_res = z[0]
      assert maker_op.random_type.values_eq(aes_res, numpy_res)
  
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 6 for calling a global function with example usage: test_random_maker_op(seed, maker_op, numpy_res) without return types