





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      A__				(       SCREAMING_SNAKE_CASE__)  ->       int:
  return EnvironmentCommand()







class        __snake_case			(				__lowerCamelCase     ):





       '''simple docstring'''







       @staticmethod
       def 				UpperCAmelCase__					(    A					:       ArgumentParser						):
         __snake_case:		int					    =		parser.add_parser("""env"""				,							help="""Print relevant system environment info."""						)
         download_parser.set_defaults(func=A						)




       def 				UpperCAmelCase__					(    self					:       Optional[int]						):
         __snake_case:		str					    =		{
             """`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(A						)						)

         return info






       @staticmethod
       def 				UpperCAmelCase__					(    A					:       Union[str, Any]						):
         return "\n".join([f'''- {prop}: {val}''' for prop, val in d.items()]						) + "\n"













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase			:  Optional[Any]										=				{"configuration_sew_d": ["SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWDConfig"]}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase			:  str										=				[
          "SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST",
          "SEWDForCTC",
          "SEWDForSequenceClassification",
          "SEWDModel",
          "SEWDPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_sew_d import (
                SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
                SEWDForCTC,
                SEWDForSequenceClassification,
                SEWDModel,
                SEWDPreTrainedModel,
            )


else:
      import sys

      __UpperCAmelCase			:  Union[str, Any]										=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






