using vertcat(MX,MX) as inputs to Function

HackyFunction.py

from casadi import *

def HackyFunction(name,ins,outs):
  # Obtain all symbolic primitives present in the inputs
  Vs = symvar(veccat(*ins))

  # Construct a helper function with these symbols as inputs
  h = Function("helper",Vs, ins)

  # Assert dense inputs
  for i in ins:
    assert i.is_dense(), "input must be dense"

  # Obtain sparsity pattern of the helper function Jacobian
  # It should be a permutation of the unit matrix
  H = blockcat([[Sparsity(h.sparsity_jac(i,j)) for i in range(h.n_in())] for j in range(h.n_out())])
  
  assert H.size1()==H.size2(), "input must be one-to-one"
  assert H.colind()==range(H.size1()+1), "input must be one-to-one"
  assert H.T.colind()==range(H.size1()+1), "input must be one-to-one"
  
  # Missing assertion: check that only transpose, reshape, vertcat, slice, .. are used

  # Construct new MX symbols on which the original inputs will depend
  Vns = [MX.sym("V",i.size()) for i in ins]

  res = reverse(ins, Vs, [Vns],{"always_inline":True,"never_inline":False})
  
  # Substitute the original inputs
  return Function("f",Vns,substitute(outs,Vs,res[0]))


# Some more tests
for M, MF in [(MX,HackyFunction), (SX,Function)]:
  x = M.sym("x")
  y = M.sym("y",1,12)
  z = M.sym("z",3,3)

  V = vertcat(y.T,x,vec(z))

  w = M.sym("w",2)
  v = M.sym("v",5)

  W = vertcat(w,v)

  f = MF("f",[V,W],[z,w,x*w])
  
  print "numerical test"

  print f(range(22),range(7))

Is there a possibility that this enters the main API?