



import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


A_		:  Optional[Any]										=  logging.get_logger(__name__)



class 		_lowercase		(							UpperCAmelCase__						):

   def __init__(   self      :							Dict				, *__lowerCAmelCase      :							Tuple				, **__lowerCAmelCase      :							List[str]				)							->					None:


    """simple docstring"""






    warnings.warn(
        "The class MaskFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
        " Please use MaskFormerImageProcessor instead."				, __lowerCAmelCase				, )
    super().__init__(*__lowerCAmelCase				, **__lowerCAmelCase				)








'''simple docstring'''






import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand
def 				_lowerCamelCase(	UpperCamelCase__     :			Any		)		->	List[str]:
    return EnvironmentCommand()





class 	_lowercase    (				a					):


   @staticmethod
   def        snake_case					(			_UpperCAmelCase       ):
       A							:							List[str]				=    parser.add_parser('''env'''     , help='''Print relevant system environment info.'''       )
       download_parser.set_defaults(func=_UpperCAmelCase       )


   def        snake_case					(			self       ):
       A							:							Optional[int]				=    {
           '''`datasets` version''': version,
           '''Platform''': platform.platform(),
           '''Python version''': platform.python_version(),
           '''Huggingface_hub version''': huggingface_hub.__version__,
           '''PyArrow version''': pyarrow.__version__,
           '''Pandas version''': pandas.__version__,
       }

       print('''\nCopy-and-paste the text below in your GitHub issue.\n'''       )
       print(self.format_dict(_UpperCAmelCase       )       )

       return info


   @staticmethod
   def        snake_case					(			_UpperCAmelCase       ):
       return "\n".join([f'''- {prop}: {val}''' for prop, val in d.items()]       ) + "\n"
