class_docstr: Fast Fourier transform.
class_docstr_tok: ["Fast","Fourier","transform","."]
code: def backward(self, inputs, grads):
      gr, gi = grads
      xp = backend.get_array_module(*grads)
      if gr is None:
          gr = xp.zeros_like(gi.data)
      if gi is None:
          gi = xp.zeros_like(gr.data)
      gxi, gxr = FFT(self._method).apply((gi, gr))
      return gxr, gxi
  
file_path: chainer/chainer/functions/math/fft.py
imports: from chainer import backend
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the FFT obj's underlying member method code with example usage: obj.backward(inputs, grads) and returns: gxr,  gxi