code: def test_vs_naive(self):
      tests = []
      try_types = (int, np.float32, np.complex64, float, complex)
  
      # Simple combinations of factors
      for x_dtype, h in product(try_types, (1.0, 1j)):
          tests.append(UpFIRDnCase(1, 1, h, x_dtype))
          tests.append(UpFIRDnCase(2, 2, h, x_dtype))
          tests.append(UpFIRDnCase(3, 2, h, x_dtype))
          tests.append(UpFIRDnCase(2, 3, h, x_dtype))
  
      # mixture of big, small, and both directions (net up and net down)
      # use all combinations of data and filter dtypes
      factors = (100, 10)  # up/down factors
      cases = product(factors, factors, try_types, try_types)
      for case in cases:
          tests += self._random_factors(*case)
  
      for test in tests:
          test()
  
file_path: catboost/contrib/python/scipy/py2/scipy/signal/tests/test_upfirdn.py
imports: import numpy
  from itertools import product
  from numpy.testing import assert_equal, assert_allclose
  from pytest import raises
  from scipy.signal import upfirdn, firwin, lfilter
  from scipy.signal._upfirdn import _output_len
label_desc: Use image node_id 3 for calling the TestUpfirdn obj's underlying member method code with example usage: obj.test_vs_naive() without return types