code: def test_fft_with_order(self, dtype, order, fft):
      # Check that FFT/IFFT produces identical results for C, Fortran and
      # non contiguous arrays
      #   rng = np.random.RandomState(42)
      rng = np.random
      X = rng.rand(8, 7, 13).astype(dtype)  # , copy=False)
      # See discussion in pull/14178
      _tol = float(
          8.0 * np.sqrt(np.log2(X.size)) * np.finfo(X.dtype).eps
      )
      if order == "F":
          raise SkipTest("Fortran order arrays")
          Y = np.asfortranarray(X)
      else:
          # Make a non contiguous array
          Z = np.empty((16, 7, 13), dtype=X.dtype)
          Z[::2] = X
          Y = Z[::2]
          X = Y.copy()
  
      if fft.__name__.endswith("fft"):
          for axis in range(3):
              X_res = fft(X, axis=axis)
              Y_res = fft(Y, axis=axis)
              assert_allclose(X_res, Y_res, atol=_tol, rtol=_tol)
      elif fft.__name__.endswith(("fft2", "fftn")):
          axes = [(0, 1), (1, 2), (0, 2)]
          if fft.__name__.endswith("fftn"):
              axes.extend([(0,), (1,), (2,), None])
          for ax in axes:
              X_res = fft(X, axes=ax)
              Y_res = fft(Y, axes=ax)
              assert_allclose(X_res, Y_res, atol=_tol, rtol=_tol)
      else:
          raise ValueError()
  
imports: import functools
  import queue
  import threading
  from unittest import skipIf, SkipTest
  import pytest
  from pytest import raises
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, TEST_WITH_TORCHDYNAMO, TestCase
label_desc: Use image node_id 20 for calling the TestFFT1D obj's underlying member method code with example usage: obj.test_fft_with_order(dtype, order, fft) without return types