code: def test_mixed_sequential_sum_product(duration, num_segments):
      sum_op, prod_op = ops.logaddexp, ops.add
      time_var = Variable("time", Bint[duration])
      step = {"_PREV_x": "x"}
  
      trans_inputs = (
          ((time_var.name, Bint[duration]),)
          + tuple((k, Bint[2]) for k in step.keys())
          + tuple((v, Bint[2]) for v in step.values())
      )
  
      trans = random_tensor(OrderedDict(trans_inputs))
  
      expected = sequential_sum_product(
          sum_op, prod_op, trans, time_var, step
      )
      actual = mixed_sequential_sum_product(
          sum_op,
          prod_op,
          trans,
          time_var,
          step,
          num_segments=num_segments,
      )
  
      assert_close(actual, expected)
  
imports: import os
  import re
  from collections import OrderedDict
  from functools import partial, reduce
  import pytest
  import funsor.ops
  from funsor.domains import Bint, Real, Reals
  from funsor.interpretations import compress_gaussians, eager, eager_or_die, lazy, moment_matching, reflect
  from funsor.interpreter import reinterpret
  from funsor.optimizer import apply_optimizer
  from funsor.sum_product import MarkovProduct, _partition, dynamic_partial_sum_product, mixed_sequential_sum_product, modified_partial_sum_product, naive_sarkka_bilmes_product, naive_sequential_sum_product, partial_sum_product, partial_unroll, sarkka_bilmes_product, sequential_sum_product, sum_product
  from funsor.tensor import Tensor, get_default_prototype
  from funsor.terms import Cat, Variable
  from funsor.testing import assert_close, random_gaussian, random_tensor
  from funsor.util import get_backend
label_desc: Use image node_id 42 for calling a global function with example usage: test_mixed_sequential_sum_product(duration, num_segments) without return types