Gurobi parallel load COBRA (.mat) model

Hi, 

I am trying to load about 300 .mat model of COBRA parallel, I used the below function:

def get_capacity_matrix_parallel(model_path, target_rxns, AD_samples, HT_samples,
                                 n_workers=16):
   all_fnames = sorted(os.listdir(model_path))
   all_fnames = [f for f in all_fnames if f.endswith('.mat')]
   n_models = len(all_fnames)

   if n_models == 0:
       raise RuntimeError(f"No .mat files found in {model_path}")

   n_workers = min(n_workers, n_models)

   AD_set = set(AD_samples)
   HT_set = set(HT_samples)

   matrix     = np.zeros((n_models, len(target_rxns)))
   phenotypes = [None] * n_models
   model_dict = {'AD': {}, 'HT': {}}
   fname_to_idx = {f: i for i, f in enumerate(all_fnames)}

   args_list = [
       (fname, model_path, target_rxns, AD_set, HT_set)
       for fname in all_fnames
   ]

   errors = []
   print(f"Loading {n_models} models with {n_workers} workers "
         f"(each worker: own Gurobi Env, Threads=1)")
   t0 = time.time()

   with Pool(processes=n_workers, initializer=_pool_initializer) as pool:
       for result in tqdm(
           pool.imap_unordered(_load_and_compute_one, args_list, chunksize=1),
           total=n_models, desc="Models",
       ):
           idx = fname_to_idx[result['fname']]
           matrix[idx]     = result['v_max_row']
           phenotypes[idx] = result['phenotype']

           if result['error']:
               errors.append((result['fname'], result['error']))
               continue

           if result['phenotype'] in ('AD', 'HT') and result['model'] is not None:
               model_dict[result['phenotype']][result['sample_id']] = result['model']

   elapsed = time.time() - t0
   print(f"\nFinished in {elapsed:.1f}s  ({elapsed/n_models:.2f}s per model avg)")

   if errors:
       print(f"\n{len(errors)} models failed:")
       for fname, err in errors[:10]:
           print(f"  {fname}: {err}")
       if len(errors) > 10:
           print(f"  ... and {len(errors) - 10} more")

   return matrix, model_dict, all_fnames, phenotypes, n_models 

But it failed to have parallel loading processes, still load the .mat model serially. Could you please give me some guidance on what should I do? Thanks!