code: def axis_assign(a, b, start=None, stop=None, step=None, axis=-1):
      """Take a slice along axis 'axis' from 'a' and set it to 'b' in-place.
  
      Parameters
      ----------
      a : numpy.ndarray
          The array to be sliced.
      b : cupy.ndarray
          The array to be assigned.
      start, stop, step : int or None
          The slice parameters.
      axis : int, optional
          The axis of `a` to be sliced.
  
      Examples
      --------
      >>> a = array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
      >>> b1 = array([[-1], [-4], [-7]])
      >>> axis_assign(a, b1, start=0, stop=1, axis=1)
      array([[-1, 2, 3],
             [-4, 5, 6],
             [-7, 8, 9]])
  
      Notes
      -----
      The keyword arguments start, stop and step are used by calling
      slice(start, stop, step). This implies axis_assign() does not
      handle its arguments the exactly the same as indexing. To assign
      a single index k, for example, use
          axis_assign(a, start=k, stop=k+1)
      In this case, the length of the axis 'axis' in the result will
      be 1; the trivial dimension is not removed. (Use numpy.squeeze()
      to remove trivial axes.)
  
      This function works in-place and will modify the values contained in `a`
      """
      a_slice = [slice(None)] * a.ndim
      a_slice[axis] = slice(start, stop, step)
      a[tuple(a_slice)] = b
      return a
  
file_path: cupy/cupyx/scipy/signal/_arraytools.py
imports: import cupy
label_desc: Use image node_id 2 for calling a global function with example usage: axis_assign(a, b, start, stop, step, axis) and returns: a