code: def test_dft(
      *,
      d_xfft_axis_n_length,
      d_xifft_axis_n_length,
      inverse,
      onesided,
      test_flags,
      backend_fw,
      fn_name,
      on_device,
  ):
      if inverse:
          dtype, x, axis, norm, dft_length = d_xifft_axis_n_length
      else:
          dtype, x, axis, norm, dft_length = d_xfft_axis_n_length
  
      helpers.test_function(
          input_dtypes=dtype,
          test_flags=test_flags,
          backend_to_test=backend_fw,
          fn_name=fn_name,
          on_device=on_device,
          x=x,
          axis=axis,
          inverse=inverse,
          onesided=onesided,
          dft_length=dft_length,
          norm=norm,
      )
  
imports: import numpy
  import torch
  from hypothesis import strategies, assume
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test, BackendHandler
label_desc: Use image node_id 21 for calling a global function with example usage: test_dft() without return types