code: def test_partial_sum_product_scale_1(sum_op, prod_op, scale):
      f1 = random_tensor(OrderedDict(a=Bint[2]))
      f2 = random_tensor(OrderedDict(a=Bint[2], i=Bint[3]))
  
      eliminate = frozenset("ai")
      plates = frozenset("i")
  
      # Actual result based on applying scaling
      factors = [f1, f2]
      scales = {"i": scale}
      actual = sum_product(
          sum_op,
          prod_op,
          factors,
          eliminate,
          plates,
          plate_to_scale=scales,
      )
  
      # Expected result based on concatenating factors
      f3 = Cat("i", (f2,) * scale)
      factors = [f1, f3]
      expected = sum_product(
          sum_op, prod_op, factors, eliminate, plates
      )
  
      assert_close(actual, expected, atol=1e-4, rtol=1e-4)
  
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 43 for calling a global function with example usage: test_partial_sum_product_scale_1(sum_op, prod_op, scale) without return types