code: def test_dct_dim(fn, dim):
      x = torch.randn(4, 5, 6, 7)
      actual = fn(x, dim=dim)
      if dim == -1 or dim == 3:
          expected = fn(x)
      else:
          expected = fn(x.transpose(-1, dim)).transpose(-1, dim)
      assert_close(actual, expected)
  
imports: import math
  import numpy
  import pytest
  import scipy.fftpack
  import torch
  import pyro
  from pyro.ops.tensor_utils import block_diag_embed, block_diagonal, convolve, dct, idct, next_fast_len, periodic_cumsum, periodic_features, periodic_repeat, precision_to_scale_tril, repeated_matmul
  from tests.common import assert_close, assert_equal
label_desc: Use image node_id 11 for calling a global function with example usage: test_dct_dim(fn, dim) without return types