I am trying to run a script written by a collaborator and am receiving the below error messages (collaborator does not have any issues with the code, so I believe this is specific to my computer, perhaps something to do with how Python/PyStan were installed). I am having difficulty understanding what the issue is and am wondering if others have any insight.
INFO:pystan:COMPILING THE C++ CODE FOR MODEL
anon_model_0d47690cf7435359b66ab970423cdb60 NOW. Traceback (most
recent call last): File
"/Users/AmyRapp/opt/anaconda3/lib/python3.8/site-packages/pystan/model.py",
line 84, in _map_parallel
pool = multiprocessing.Pool(processes=n_jobs) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/context.py",
line 119, in Pool
return Pool(processes, initializer, initargs, maxtasksperchild, File
"/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/pool.py",
line 212, in init
self._repopulate_pool() File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/pool.py",
line 303, in _repopulate_pool
return self._repopulate_pool_static(self._ctx, self.Process, File
"/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/pool.py",
line 326, in _repopulate_pool_static
w.start() File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/process.py",
line 121, in start
self._popen = self._Popen(self) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/context.py",
line 284, in _Popen
return Popen(process_obj) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/popen_spawn_posix.py",
line 32, in init
super().init(process_obj) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/popen_fork.py",
line 19, in init
self._launch(process_obj) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/popen_spawn_posix.py",
line 42, in _launch
prep_data = spawn.get_preparation_data(process_obj._name) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/spawn.py",
line 154, in get_preparation_data
_check_not_importing_main() File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/spawn.py",
line 134, in _check_not_importing_main
raise RuntimeError(''' RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "", line 1, in
File
"/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/spawn.py",
line 116, in spawn_main
exitcode = _main(fd, parent_sentinel) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/spawn.py",
line 125, in _main
prepare(preparation_data) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/spawn.py",
line 236, in prepare
_fixup_main_from_path(data['init_main_from_path']) File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/multiprocessing/spawn.py",
line 287, in _fixup_main_from_path
main_content = runpy.run_path(main_path, File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/runpy.py", line 265, in
run_path
return _run_module_code(code, init_globals, run_name, File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/runpy.py", line 97, in
_run_module_code
_run_code(code, mod_globals, init_globals, File "/Users/AmyRapp/opt/anaconda3/lib/python3.8/runpy.py", line 87, in
_run_code
exec(code, run_globals) File "/Users/AmyRapp/Desktop/Galaxy/pystan_fitting_sub_nos_v301.py", line
225, in
fit_dec = dec.sampling(data=data, iter=n_iter, chains=n_chains, warmup=n_warmup, thin=1, seed=seed_val,verbose=True) File
"/Users/AmyRapp/opt/anaconda3/lib/python3.8/site-packages/pystan/model.py",
line 813, in sampling
ret_and_samples = _map_parallel(call_sampler_star, call_sampler_args, n_jobs) File
"/Users/AmyRapp/opt/anaconda3/lib/python3.8/site-packages/pystan/model.py",
line 87, in _map_parallel
pool.close()
