code: def uniform_filter(
      input, size=3, output=None, mode="reflect", cval=0.0, origin=0
  ):
      """Multi-dimensional uniform filter.
  
      Args:
          input (cupy.ndarray): The input array.
          size (int or sequence of int): Lengths of the uniform filter for each
              dimension. A single value applies to all axes.
          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.uniform_filter`
  
      .. note::
          When the output data type is integral (or when no output is provided
          and input is integral) the results may not perfectly match the results
          from SciPy due to floating-point rounding of intermediate results.
      """
      sizes = _util._fix_sequence_arg(size, input.ndim, "size", int)
      weights_dtype = _util._init_weights_dtype(input)
  
      def get(size, dtype=weights_dtype):
          return (
              None
              if size <= 1
              else cupy.full(size, 1 / size, dtype=dtype)
          )
  
      return _run_1d_correlates(
          input, sizes, get, 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 9 for calling a global function with example usage: uniform_filter(input, size, output, mode, cval, origin) and returns: _run_1d_correlates, unknown