code: def test_elemwise_speed(benchmark):
      x = pt.dmatrix("y")
      y = pt.dvector("z")
  
      out = np.exp(2 * x * y + y)
  
      rng = np.random.default_rng(42)
  
      x_val = rng.normal(size=(200, 500))
      y_val = rng.normal(size=500)
  
      func = function([x, y], out, mode="NUMBA")
      func = func.vm.jit_fn
      (out,) = func(x_val, y_val)
      np.testing.assert_allclose(np.exp(2 * x_val * y_val + y_val), out)
  
      benchmark(func, x_val, y_val)
  
imports: import contextlib
  import numpy
  import pytest
  import scipy.special
  import pytensor
  import pytensor.tensor
  import pytensor.tensor.inplace
  import pytensor.tensor.math
  from pytensor import config, function
  from pytensor.compile import get_mode
  from pytensor.compile.ops import deep_copy_op
  from pytensor.compile.sharedvalue import SharedVariable
  from pytensor.gradient import grad
  from pytensor.graph.basic import Constant
  from pytensor.graph.fg import FunctionGraph
  from pytensor.tensor import elemwise
  from pytensor.tensor.math import All, Any, Max, Mean, Min, Prod, ProdWithoutZeros, Sum
  from pytensor.tensor.special import LogSoftmax, Softmax, SoftmaxGrad
  from tests.link.numba.test_basic import compare_numba_and_py, scalar_my_multi_out, set_test_value
  from tests.tensor.test_elemwise import TestElemwise
label_desc: Use image node_id 3 for calling a global function with example usage: test_elemwise_speed(benchmark) without return types