code: def test_local_mul_s_v():
      mode = get_default_mode()
      mode = mode.including("specialize", "local_mul_s_v")
  
      for sp_format in ["csr"]:  # Not implemented for other format
          inputs = [
              getattr(pytensor.sparse, sp_format + "_matrix")(),
              vector(),
          ]
  
          f = pytensor.function(
              inputs, sparse.mul_s_v(*inputs), mode=mode
          )
  
          assert not any(
              isinstance(node.op, sparse.MulSV)
              for node in f.maker.fgraph.toposort()
          )
  
imports: import numpy
  import pytest
  import scipy
  import pytensor
  from pytensor import sparse
  from pytensor.compile.mode import Mode, get_default_mode
  from pytensor.configdefaults import config
  from pytensor.sparse.rewriting import SamplingDotCSR, sd_csc
  from pytensor.tensor.basic import as_tensor_variable
  from pytensor.tensor.math import sum
  from pytensor.tensor.type import ivector, matrix, vector
  from tests import unittest_tools
  from tests.sparse.test_basic import random_lil
label_desc: Use image node_id 4 for calling a global function with example usage: test_local_mul_s_v() without return types