
'''simple docstring'''

from typing import TYPE_CHECKING

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


UpperCamelCase_            =    {
    """configuration_ernie_m""": ["""ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieMConfig"""],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase_            =    ["""ErnieMTokenizer"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase_            =    [
         """ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """ErnieMForMultipleChoice""",
         """ErnieMForQuestionAnswering""",
         """ErnieMForSequenceClassification""",
         """ErnieMForTokenClassification""",
         """ErnieMModel""",
         """ErnieMPreTrainedModel""",
         """ErnieMForInformationExtraction""",
     ]


if TYPE_CHECKING:
     from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_ernie_m import ErnieMTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_ernie_m import (
              ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
              ErnieMForInformationExtraction,
              ErnieMForMultipleChoice,
              ErnieMForQuestionAnswering,
              ErnieMForSequenceClassification,
              ErnieMForTokenClassification,
              ErnieMModel,
              ErnieMPreTrainedModel,
          )


else:
     import sys

     UpperCamelCase_            =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




'''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 		_UpperCAmelCase			(					_lowerCamelCase  :    List[Any]						)      ->  Optional[Any]:
  return EnvironmentCommand()



class 					a_					(_a      ):




       @staticmethod
       def 							__UpperCamelCase    (       snake_case_					):
         _lowerCAmelCase    :					Optional[Any]							=   parser.add_parser("""env"""				,				help="""Print relevant system environment info."""					)
         download_parser.set_defaults(func=snake_case_					)




       def 							__UpperCamelCase    (       self					):
         _lowerCAmelCase    :					Optional[Any]							=   {
             """`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(snake_case_					)					)

         return info







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


