JoshBroomberg / Maccabee

Hybrid Monte Carlo Benchmarks for Methods of Causal Inference
https://maccabee.readthedocs.io/en/latest/
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Multiprocessing RuntimeError #2

Open pelegshilo opened 1 year ago

pelegshilo commented 1 year ago

Hi,

I'm trying to run the basic code from the tutorial and I'm getting the following error:

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\spawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\spawn.py", line 125, in _main
    prepare(preparation_data)
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\spawn.py", line 236, in prepare
    _fixup_main_from_path(data['init_main_from_path'])
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path
    main_content = runpy.run_path(main_path,
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\runpy.py", line 268, in run_path
    return _run_module_code(code, init_globals, run_name,
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\runpy.py", line 97, in _run_module_code
    _run_code(code, mod_globals, init_globals,
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\peleg\PycharmProjects\imodels-bestsubsetrules\tests\Maccabee tests.py", line 38, in <module>
    results = benchmark_model_using_sampled_dgp_grid(
  File "C:\Users\peleg\PycharmProjects\imodels-bestsubsetrules\venv\lib\site-packages\maccabee\benchmarking\benchmarking.py", line 474, in benchmark_model_using_sampled_dgp_grid
    benchmark_model_using_sampled_dgp(
  File "C:\Users\peleg\PycharmProjects\imodels-bestsubsetrules\venv\lib\site-packages\maccabee\benchmarking\benchmarking.py", line 371, in benchmark_model_using_sampled_dgp
    dgps = robust_parallel_map(
  File "C:\Users\peleg\PycharmProjects\imodels-bestsubsetrules\venv\lib\site-packages\maccabee\utilities\multiprocessing.py", line 123, in robust_parallel_map
    manager = Manager()
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\context.py", line 57, in Manager
    m.start()
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\managers.py", line 553, in start
    self._process.start()
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\process.py", line 121, in start
    self._popen = self._Popen(self)
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\context.py", line 327, in _Popen
    return Popen(process_obj)
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__
    prep_data = spawn.get_preparation_data(process_obj._name)
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\multiprocessing\spawn.py", line 154, in get_preparation_data
    _check_not_importing_main()
  File "C:\Users\peleg\AppData\Local\Programs\Python\Python39\lib\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.

This issue means I am unable to use the library. Can you please look at it?

pelegshilo commented 1 year ago

For additional information, this is the code that I'm trying to run


results = benchmark_model_using_sampled_dgp_grid(
    model_class=LinearRegressionCausalModel,
    estimand=Constants.Model.ATE_ESTIMAND,
    data_source=normal_data_source,
    dgp_param_grid=param_grid,
    num_dgp_samples=2,
    num_sampling_runs_per_dgp=2,
    num_samples_from_dgp=96)```