code: def ifftn(x, shape=None, axes=None, overwrite_x=False, plan=None):
      """Compute the N-dimensional inverse FFT.
  
      Args:
          x (cupy.ndarray): Array to be transformed.
          shape (None or tuple of ints): Shape of the transformed axes of the
              output. If ``shape`` is not given, the lengths of the input along
              the axes specified by ``axes`` are used.
          axes (tuple of ints): Axes over which to compute the FFT.
          overwrite_x (bool): If True, the contents of ``x`` can be destroyed.
          plan (:class:`cupy.cuda.cufft.PlanNd` or ``None``): a cuFFT plan for
              transforming ``x`` over ``axes``, which can be obtained using::
  
                  plan = cupyx.scipy.fftpack.get_fft_plan(x, axes)
  
              Note that `plan` is defaulted to None, meaning CuPy will either
              use an auto-generated plan behind the scene if cupy.fft.config.
              enable_nd_planning = True, or use no cuFFT plan if it is set to
              False.
  
      Returns:
          cupy.ndarray:
              The transformed array which shape is specified by ``shape`` and
              type will convert to complex if that of the input is another.
  
      .. seealso:: :func:`scipy.fftpack.ifftn`
  
      .. note::
         The argument `plan` is currently experimental and the interface may be
         changed in the future version.
      """
      from cupy.cuda import cufft
  
      func = _default_fft_func(x, shape, axes, plan)
      return func(
          x,
          shape,
          axes,
          None,
          cufft.CUFFT_INVERSE,
          overwrite_x=overwrite_x,
          plan=plan,
      )
  
file_path: cupy/cupyx/scipy/fftpack/_fft.py
imports: from numpy import prod
  import cupy
  from cupy.fft import config
  from cupy.fft._fft import _convert_fft_type, _default_fft_func, _fft, _get_cufft_plan_nd, _get_fftn_out_size, _output_dtype
  from cupy.fft._cache import get_plan_cache
label_desc: Use image node_id 7 for calling a global function with example usage: ifftn(x, shape, axes, overwrite_x, plan) and returns: func