code: def test_RandomVariable_incompatible_size():
      rv_op = RandomVariable(
          "normal", 0, [0, 0], config.floatX, inplace=True
      )
      with pytest.raises(
          ValueError,
          match="Size length is incompatible with batched dimensions",
      ):
          rv_op(np.zeros((1, 3)), 1, size=(3,))
  
      rv_op = RandomVariable(
          "dirichlet", 0, [1], config.floatX, inplace=True
      )
      with pytest.raises(
          ValueError,
          match="Size length is incompatible with batched dimensions",
      ):
          rv_op(np.zeros((2, 4, 3)), 1, size=(4,))
  
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 8 for calling a global function with example usage: test_RandomVariable_incompatible_size() without return types