code: def test_RandomVariable_floatX():
      test_rv_op = RandomVariable(
          "normal",
          0,
          [0, 0],
          "floatX",
          inplace=True,
      )
  
      assert test_rv_op.dtype == "floatX"
  
      assert test_rv_op(0, 1).dtype == config.floatX
  
      new_floatX = (
          "float64" if config.floatX == "float32" else "float32"
      )
  
      with config.change_flags(floatX=new_floatX):
          assert test_rv_op(0, 1).dtype == new_floatX
  
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 5 for calling a global function with example usage: test_RandomVariable_floatX() without return types