Atom type overflow in Topology due to int8

[bctapia]

When generating the fragment input files, I received the error

Traceback (most recent call last):
  File "/home/gridsan/btapia/.conda/envs/polypal/bin/qforce", line 7, in <module>
    sys.exit(run())
             ^^^^^
  File "/home/gridsan/btapia/.conda/envs/polypal/lib/python3.12/site-packages/colt/colt.py", line 363, in __call__
    return self._func(**answers)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/home/gridsan/btapia/.conda/envs/polypal/lib/python3.12/site-packages/qforce/main.py", line 37, in run
    run_qforce(input_arg=file, config=options)
  File "/home/gridsan/btapia/.conda/envs/polypal/lib/python3.12/site-packages/qforce/main.py", line 49, in run_qforce
    mol = Molecule(config, job, qm_hessian_out, ext_q, ext_lj)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/gridsan/btapia/.conda/envs/polypal/lib/python3.12/site-packages/qforce/molecule/molecule.py", line 14, in __init__
    self.topo = Topology(config.ff, qm_out)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/gridsan/btapia/.conda/envs/polypal/lib/python3.12/site-packages/qforce/molecule/topology.py", line 31, in __init__
    self._setup(qm_out)
  File "/home/gridsan/btapia/.conda/envs/polypal/lib/python3.12/site-packages/qforce/molecule/topology.py", line 35, in _setup
    self._find_atom_types()
  File "/home/gridsan/btapia/.conda/envs/polypal/lib/python3.12/site-packages/qforce/molecule/topology.py", line 94, in _find_atom_types
    self.atoms[eq] = self.n_types
    ~~~~~~~~~~^^^^
OverflowError: Python integer 128 out of bounds for int8

Which appears to be due to the fact that Q-Force caps the number of atom types at 128 due to using int8.

I propose replacing
self.atoms = np.zeros(self.n_atoms, dtype='int8')
with
self.atoms = np.zeros(self.n_atoms, dtype='int16')
In line 28 of qforce.molecule.topology.py
To remove any chance this error occurs while also attempting to limit memory usage as much as possible. Alternatively, if memory is significantly affected, self.atoms = np.zeros(self.n_atoms, dtype='uint8') could be considered.

My settings script is

[ff]
n_equiv = 4
n_excl = 2
lennard_jones = opls
ext_charges = no
charge_scaling = 1.2
use_ext_charges_for_frags = no
ext_lj_lib =
ext_lj_fudge =
ext_q_fudge =
ext_comb_rule =
ext_h_cap =
all_rigid = no
res_name = MOL

[qm]
software = orca
scan_step_size = 15.0
charge = 0
multiplicity = 1
memory = 120000
n_proc = 32
vib_scaling = 0.97
dihedral_scanner = relaxed_scan

[qm::software(orca)]
charge_method = esp
qm_method_opt = r2SCAN-3c
qm_method_hessian = r2SCAN-3c
qm_method_charge = HF 6-31G*
qm_method_sp = r2SCAN-3c

[scan]
do_scan = yes
avail_only = no
frag_threshold = 3
conj_bo_cutoff = 1.4
break_co_bond = no
method = gromacs
gromacs_exec = /home/gridsan/btapia/programs/gromacs-cpu/bin/gmx_mpi
n_dihed_scans = 15
plot_fit = yes
batch_run = False

[terms]
urey = True
dihedral/rigid = True
dihedral/improper = True
dihedral/flexible = True
dihedral/inversion = True
non_bonded = True

My geometry optimized molecule looks as I expected.