code: def grad_concatenate_args(argnum, ans, axis_args, kwargs):
      axis, args = axis_args[0], axis_args[1:]
      sizes = [anp.shape(a)[axis] for a in args[:argnum]]
      start = sum(sizes[:-1])
      idxs = [slice(None)] * ans.ndim
      idxs[axis] = slice(start, start + sizes[-1])
      return lambda g: g[tuple(idxs)]
  
imports: from __future__ import absolute_import
  from six import string_types
  from functools import partial
  import numpy
  from ..util import func
  from .None import numpy_wrapper
  from .numpy_boxes import ArrayBox
  from autograd.extend import primitive, vspace, defvjp, defvjp_argnum, SparseObject, VJPNode, register_notrace
label_desc: Use image node_id 31 for calling a global function with example usage: grad_concatenate_args(argnum, ans, axis_args, kwargs) and returns: function