code: def test_multivariate_rv_infer_static_shape():
      """Test that infer shape for multivariate random variable works when a parameter must be broadcasted."""
      mv_op = MultivariateRandomVariable()
  
      param1 = tensor(shape=(10, 2, 3))
      param2 = tensor(shape=(10, 2, 3, 3))
      assert mv_op(param1, param2).type.shape == (10, 2, 3)
  
      param1 = tensor(shape=(2, 3))
      param2 = tensor(shape=(10, 2, 3, 3))
      assert mv_op(param1, param2).type.shape == (10, 2, 3)
  
      param1 = tensor(shape=(10, 2, 3))
      param2 = tensor(shape=(2, 3, 3))
      assert mv_op(param1, param2).type.shape == (10, 2, 3)
  
      param1 = tensor(shape=(10, 1, 3))
      param2 = tensor(shape=(2, 3, 3))
      assert mv_op(param1, param2).type.shape == (10, 2, 3)
  
      param1 = tensor(shape=(2, 3))
      param2 = tensor(shape=(2, 3, 3))
      assert mv_op(param1, param2, size=(10, 2)).type.shape == (
          10,
          2,
          3,
      )
  
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 9 for calling a global function with example usage: test_multivariate_rv_infer_static_shape() without return types