




import argparse
import os

from accelerate.test_utils import execute_subprocess_async







def SCREAMING_SNAKE_CASE    (	lowercase_=None						)       ->	List[str]:



    """simple docstring"""

    if subparsers is not None:
        A__							=   subparsers.add_parser('''test'''						)
    else:
        A__							=   argparse.ArgumentParser('''Accelerate test command'''						)

    parser.add_argument(
        '''--config_file'''			,    default=__UpperCAmelCase			,    help=(
            '''The path to use to store the config file. Will default to a file named default_config.yaml in the cache '''
            '''location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '''
            '''such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '''
            '''with \'huggingface\'.'''
        )			,    )

    if subparsers is not None:
        parser.set_defaults(func=__UpperCAmelCase						)
    return parser







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	List[str]:



    """simple docstring"""

    A__							=   os.path.sep.join(__file__.split(os.path.sep						)[:-2] + ['''test_utils''', '''scripts''', '''test_script.py''']						)

    if args.config_file is None:
        A__							=   script_name
    else:
        A__							=   f"""--config_file={args.config_file} {script_name}"""

    A__							=   ['''accelerate-launch'''] + test_args.split()
    A__							=   execute_subprocess_async(__UpperCAmelCase			,    env=os.environ.copy()						)
    if result.returncode == 0:
        print('''Test is a success! You are ready for your distributed training!'''						)







def SCREAMING_SNAKE_CASE    (	)       ->	Optional[int]:



    """simple docstring"""

    A__							=   test_command_parser()
    A__							=   parser.parse_args()
    test_command(__UpperCAmelCase						)


if __name__ == "__main__":
  main()








from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase     :		str								=       {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Dict								=       [
      """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """FocalNetForImageClassification""",
      """FocalNetForMaskedImageModeling""",
      """FocalNetBackbone""",
      """FocalNetModel""",
      """FocalNetPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_focalnet import (
        FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        FocalNetBackbone,
        FocalNetForImageClassification,
        FocalNetForMaskedImageModeling,
        FocalNetModel,
        FocalNetPreTrainedModel,
    )

else:
  import sys

  _lowerCamelCase     :		Tuple								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


