code: def median_filter(
      input,
      size=None,
      footprint=None,
      output=None,
      mode="reflect",
      cval=0.0,
      origin=0,
  ):
      """Multi-dimensional median filter.
  
      Args:
          input (cupy.ndarray): The input array.
          size (int or sequence of int): One of ``size`` or ``footprint`` must be
              provided. If ``footprint`` is given, ``size`` is ignored. Otherwise
              ``footprint = cupy.ones(size)`` with ``size`` automatically made to
              match the number of dimensions in ``input``.
          footprint (cupy.ndarray): a boolean array which specifies which of the
              elements within this shape will get passed to the filter function.
          output (cupy.ndarray, dtype or None): The array in which to place the
              output. Default is is same dtype as the input.
          mode (str): The array borders are handled according to the given mode
              (``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
              ``'wrap'``). Default is ``'reflect'``.
          cval (scalar): Value to fill past edges of input if mode is
              ``'constant'``. Default is ``0.0``.
          origin (int or sequence of int): The origin parameter controls the
              placement of the filter, relative to the center of the current
              element of the input. Default of 0 is equivalent to
              ``(0,)*input.ndim``.
  
      Returns:
          cupy.ndarray: The result of the filtering.
  
      .. seealso:: :func:`scipy.ndimage.median_filter`
      """
      return _rank_filter(
          input,
          lambda fs: fs // 2,
          size,
          footprint,
          output,
          mode,
          cval,
          origin,
      )
  
imports: import numpy
  import cupy
  from cupy import _core
  from cupy._core import internal
  from cupyx.scipy.ndimage import _util
  from cupyx.scipy.ndimage import _filters_core
  from cupyx.scipy.ndimage import _filters_generic
label_desc: Use image node_id 29 for calling a global function with example usage: median_filter(input, size, footprint, output, mode, cval, origin) and returns: _rank_filter