Maximizing $(x-5)^2$ subject to $0 \leqslant x \leqslant 10$

Question

I am working on a simple case of convex optimization. I modeled the system on paper and now am using Python the RSOME library. I want to maximise $(x-5)^2$ (bounded between $0 \leqslant x \leqslant 10$) but the code keeps telling me that this is a nonconvex case. Does anyone know if it is nonconvex? a positive parabola is fundamentally convex no?

Here is my Python code:

import rsome as rso
import numpy as np
from rsome import ro
from rsome import dro
from rsome import E     
#from rsome import eco_solver as grb
from rsome import grb_solver as grb
model = dro.Model('test')            # create an RSOME model

x = model.dvar()



model.max(rso.square(x-5)) #working
#model.st(rso.square(x-5) <= 100)
#model.st(x <= 10)
#model.st(rso.square(x-5))


model.st(x= >= 0)
model.st(x <= 5)

model.solve(grb)

print(x.get())

user_value = x.get()

Here are the error messages:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-21-ffa94a01dc07> in <module>
     21 model.st((x-5) <= 5)
     22 
---> 23 model.solve(grb)
     24 
     25 print(x.get())

3 frames
/usr/local/lib/python3.8/dist-packages/rsome/lp.py in __ge__(self, other)
   2935         elif isinstance(left, DecConvex):
   2936             if left.sign == -1:
-> 2937                 raise ValueError('Nonconvex constraints.')
   2938             return DecCvxConstr(left, left.event_adapt)
   2939         elif isinstance(left, DecPerspConvex):

ValueError: Nonconvex constraints.