old_contents: from chainer import cuda
  from chainer import function_node
  from chainer.utils import type_check
  
  
  class FFT(function_node.FunctionNode):
  
      """Fast Fourie transform."""
  
      def __init__(self, method):
          self._method = method
  
      def check_type_forward(self, in_types):
          type_check.expect(in_types.size() == 2)
          r_type, i_type = in_types
          type_check.expect(
              r_type.dtype.kind == 'f',
              r_type.ndim > 0,
              r_type.shape == i_type.shape,
              r_type.dtype == i_type.dtype,
          )
  
      def forward(self, inputs):
          xp = cuda.get_array_module(*inputs)
          real, imag = inputs
          x = real + imag * 1j
          y = getattr(xp.fft, self._method)(x)
          real_y = y.real.astype(real.dtype)
          imag_y = y.imag.astype(imag.dtype)
          return real_y, imag_y
  
      def backward(self, inputs, grads):
          gr, gi = grads
          gxi, gxr = FFT(self._method).apply((gi, gr))
          return gxr, gxi
  
  
  def fft(real, imag):
      """Fast Fourie transform.
  
      Args:
          real (chainer.Variable): Real part of the input.
          imag (chainer.Variable): Imaginary part of the input.
  
      Returns:
          tuple: Returns ``(ry, ri)`` where ``ry`` is the real part of
          the result and ``ri`` is the imaginary part of the result.
  
      """
      return FFT('fft').apply((real, imag))
  
  
  def ifft(real, imag):
      """Inverse fast Fourie transform.
  
      Args:
          real (chainer.Variable): Real part of the input.
          imag (chainer.Variable): Imaginary part of the input.
  
      Returns:
          tuple: Returns ``(ry, ri)`` where ``ry`` is the real part of
          the result and ``ri`` is the imaginary part of the result.
  
      """
      return FFT('ifft').apply((real, imag))
  
new_contents: from chainer import cuda
  from chainer import function_node
  from chainer.utils import type_check
  
  
  class FFT(function_node.FunctionNode):
  
      """Fast Fourier transform."""
  
      def __init__(self, method):
          self._method = method
  
      def check_type_forward(self, in_types):
          type_check.expect(in_types.size() == 2)
          r_type, i_type = in_types
          type_check.expect(
              r_type.dtype.kind == 'f',
              r_type.ndim > 0,
              r_type.shape == i_type.shape,
              r_type.dtype == i_type.dtype,
          )
  
      def forward(self, inputs):
          xp = cuda.get_array_module(*inputs)
          real, imag = inputs
          x = real + imag * 1j
          y = getattr(xp.fft, self._method)(x)
          real_y = y.real.astype(real.dtype)
          imag_y = y.imag.astype(imag.dtype)
          return real_y, imag_y
  
      def backward(self, inputs, grads):
          gr, gi = grads
          gxi, gxr = FFT(self._method).apply((gi, gr))
          return gxr, gxi
  
  
  def fft(real, imag):
      """Fast Fourier transform.
  
      Args:
          real (chainer.Variable): Real part of the input.
          imag (chainer.Variable): Imaginary part of the input.
  
      Returns:
          tuple: Returns ``(ry, ri)`` where ``ry`` is the real part of
          the result and ``ri`` is the imaginary part of the result.
  
      """
      return FFT('fft').apply((real, imag))
  
  
  def ifft(real, imag):
      """Inverse fast Fourier transform.
  
      Args:
          real (chainer.Variable): Real part of the input.
          imag (chainer.Variable): Imaginary part of the input.
  
      Returns:
          tuple: Returns ``(ry, ri)`` where ``ry`` is the real part of
          the result and ``ri`` is the imaginary part of the result.
  
      """
      return FFT('ifft').apply((real, imag))
  
subject: Fix typo