import os

import pytest

from transformers.dynamic_module_utils import get_imports


lowerCAmelCase			:							str     ="\nimport os\n"

lowerCAmelCase			:							int     ="\ndef foo():\n    import os\n    return False\n"

lowerCAmelCase			:							Optional[int]     ="\ndef foo():\n    def bar():\n        if True:\n            import os\n        return False\n    return bar()\n"

lowerCAmelCase			:							List[Any]     ="\nimport os\n\ntry:\n    import bar\nexcept ImportError:\n    raise ValueError()\n"

lowerCAmelCase			:							Dict     ="\nimport os\n\ndef foo():\n    try:\n        import bar\n    except ImportError:\n        raise ValueError()\n"

lowerCAmelCase			:							Union[str, Any]     ="\nimport os\n\ntry:\n    import bar\nexcept (ImportError, AttributeError):\n    raise ValueError()\n"

lowerCAmelCase			:							Any     ="\nimport os\n\ntry:\n    import bar\nexcept ImportError as e:\n    raise ValueError()\n"

lowerCAmelCase			:							Tuple     ="\nimport os\n\ntry:\n    import bar\nexcept:\n    raise ValueError()\n"

lowerCAmelCase			:							Optional[Any]     ="\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    raise ValueError()\n"

lowerCAmelCase			:							Optional[Any]     ="\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    x = 1\n    raise ValueError()\n"

lowerCAmelCase			:							Optional[Any]     =[
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]







@pytest.mark.parametrize("""case"""   , __A	)
def 						A__  (					__A   , __A	):







    '''simple docstring'''
    _lowerCamelCase     :		Tuple 						=						os.path.join(__A   , """test_file.py"""	)
    with open(__A   , """w"""	) as _tmp_file:
        _tmp_file.write(__A	)

    _lowerCamelCase     :		Optional[int] 						=						get_imports(__A	)
    assert parsed_imports == ["os"]





import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		Optional[int] 						=						ArgumentParser(
        description=(
            """PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes"""
        )	)

    # Optional arguments for the launch helper
    parser.add_argument("""--num_cores"""   , type=__A   , default=1   , help="""Number of TPU cores to use (1 or 8)."""	)

    # positional
    parser.add_argument(
        """training_script"""   , type=__A   , help=(
            """The full path to the single TPU training """
            """program/script to be launched in parallel, """
            """followed by all the arguments for the """
            """training script"""
        )   , )

    # rest from the training program
    parser.add_argument("""training_script_args"""   , nargs=__A	)

    return parser.parse_args()







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		List[str] 						=						parse_args()

    # Import training_script as a module.
    _lowerCamelCase     :		List[Any] 						=						Path(args.training_script	)
    sys.path.append(str(script_fpath.parent.resolve()	)	)
    _lowerCamelCase     :		Optional[Any] 						=						script_fpath.stem
    _lowerCamelCase     :		Dict 						=						importlib.import_module(__A	)

    # Patch sys.argv
    _lowerCamelCase     :		Union[str, Any] 						=						[args.training_script] + args.training_script_args + ["""--tpu_num_cores""", str(args.num_cores	)]

    xmp.spawn(mod._mp_fn   , args=()   , nprocs=args.num_cores	)


if __name__ == "__main__":
    main()




