code: def fft2(
      x,
      s=None,
      axes=(-2, -1),
      norm=None,
      overwrite_x=False,
      workers=None,
      *,
      plan=None,
  ):
      """
      Compute the 2-D discrete Fourier Transform
  
      This function computes the N-D discrete Fourier Transform
      over any axes in an M-D array by means of the
      Fast Fourier Transform (FFT). By default, the transform is computed over
      the last two axes of the input array, i.e., a 2-dimensional FFT.
  
      Parameters
      ----------
      x : array_like
          Input array, can be complex
      s : sequence of ints, optional
          Shape (length of each transformed axis) of the output
          (``s[0]`` refers to axis 0, ``s[1]`` to axis 1, etc.).
          This corresponds to ``n`` for ``fft(x, n)``.
          Along each axis, if the given shape is smaller than that of the input,
          the input is cropped. If it is larger, the input is padded with zeros.
          if `s` is not given, the shape of the input along the axes specified
          by `axes` is used.
      axes : sequence of ints, optional
          Axes over which to compute the FFT. If not given, the last two axes are
          used.
      norm : {"backward", "ortho", "forward"}, optional
          Normalization mode (see `fft`). Default is "backward".
      overwrite_x : bool, optional
          If True, the contents of `x` can be destroyed; the default is False.
          See :func:`fft` for more details.
      workers : int, optional
          Maximum number of workers to use for parallel computation. If negative,
          the value wraps around from ``os.cpu_count()``.
          See :func:`~scipy.fft.fft` for more details.
      plan : object, optional
          This argument is reserved for passing in a precomputed plan provided
          by downstream FFT vendors. It is currently not used in SciPy.
  
          .. versionadded:: 1.5.0
  
      Returns
      -------
      out : complex ndarray
          The truncated or zero-padded input, transformed along the axes
          indicated by `axes`, or the last two axes if `axes` is not given.
  
      Raises
      ------
      ValueError
          If `s` and `axes` have different length, or `axes` not given and
          ``len(s) != 2``.
      IndexError
          If an element of `axes` is larger than the number of axes of `x`.
  
      See Also
      --------
      ifft2 : The inverse 2-D FFT.
      fft : The 1-D FFT.
      fftn : The N-D FFT.
      fftshift : Shifts zero-frequency terms to the center of the array.
          For 2-D input, swaps first and third quadrants, and second
          and fourth quadrants.
  
      Notes
      -----
      `fft2` is just `fftn` with a different default for `axes`.
  
      The output, analogously to `fft`, contains the term for zero frequency in
      the low-order corner of the transformed axes, the positive frequency terms
      in the first half of these axes, the term for the Nyquist frequency in the
      middle of the axes and the negative frequency terms in the second half of
      the axes, in order of decreasingly negative frequency.
  
      See `fftn` for details and a plotting example, and `fft` for
      definitions and conventions used.
  
  
      Examples
      --------
      >>> import scipy.fft
      >>> import numpy as np
      >>> x = np.mgrid[:5, :5][0]
      >>> scipy.fft.fft2(x)
      array([[ 50.  +0.j        ,   0.  +0.j        ,   0.  +0.j        , # may vary
                0.  +0.j        ,   0.  +0.j        ],
             [-12.5+17.20477401j,   0.  +0.j        ,   0.  +0.j        ,
                0.  +0.j        ,   0.  +0.j        ],
             [-12.5 +4.0614962j ,   0.  +0.j        ,   0.  +0.j        ,
                0.  +0.j        ,   0.  +0.j        ],
             [-12.5 -4.0614962j ,   0.  +0.j        ,   0.  +0.j        ,
                0.  +0.j        ,   0.  +0.j        ],
             [-12.5-17.20477401j,   0.  +0.j        ,   0.  +0.j        ,
                0.  +0.j        ,   0.  +0.j        ]])
  
      """
      return (Dispatchable(x, np.ndarray),)
  
imports: from scipy._lib.uarray import generate_multimethod, Dispatchable
  import numpy
label_desc: Use image node_id 11 for calling a global function with example usage: fft2(x, s, axes, norm, overwrite_x, workers) and returns: Dispatchable