





'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase      :  Dict      							={
    '''configuration_splinter''': ['''SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SplinterConfig'''],
    '''tokenization_splinter''': ['''SplinterTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase      :  Optional[Any]      							=['''SplinterTokenizerFast''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase      :  int      							=[
     '''SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''SplinterForQuestionAnswering''',
     '''SplinterForPreTraining''',
     '''SplinterLayer''',
     '''SplinterModel''',
     '''SplinterPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
 from .tokenization_splinter import SplinterTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_splinter_fast import SplinterTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_splinter import (
      SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
      SplinterForPreTraining,
      SplinterForQuestionAnswering,
      SplinterLayer,
      SplinterModel,
      SplinterPreTrainedModel,
  )


else:
 import sys

 lowerCAmelCase      :  Union[str, Any]      							=_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      :      Optional[int]				):
   return EnvironmentCommand()


class    a_     (       _lowerCAmelCase							):





     @staticmethod
     def 							lowercase__   (				lowercase	:      ArgumentParser		):





        """simple docstring"""




        lowercase_    :Optional[int]					    =				parser.add_parser("env"			,   help="Print relevant system environment info."		)
        download_parser.set_defaults(func=lowercase		)





     def 							lowercase__   (				self	:      List[str]		):





        """simple docstring"""




        lowercase_    :Tuple					    =				{
            "`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(lowercase		)		)

        return info







     @staticmethod
     def 							lowercase__   (				lowercase	:      Dict		):





        """simple docstring"""




        return "\n".join([F'- {prop}: {val}' for prop, val in d.items()]		) + "\n"


