



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a_								=   {
    """configuration_camembert""": ["""CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CamembertConfig""", """CamembertOnnxConfig"""],
}

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

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_								=   ["""CamembertTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_								=   [
      """CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """CamembertForCausalLM""",
      """CamembertForMaskedLM""",
      """CamembertForMultipleChoice""",
      """CamembertForQuestionAnswering""",
      """CamembertForSequenceClassification""",
      """CamembertForTokenClassification""",
      """CamembertModel""",
      """CamembertPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_								=   [
      """TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFCamembertForCausalLM""",
      """TFCamembertForMaskedLM""",
      """TFCamembertForMultipleChoice""",
      """TFCamembertForQuestionAnswering""",
      """TFCamembertForSequenceClassification""",
      """TFCamembertForTokenClassification""",
      """TFCamembertModel""",
      """TFCamembertPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_camembert import CamembertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_camembert_fast import CamembertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_camembert import (
        CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        CamembertForCausalLM,
        CamembertForMaskedLM,
        CamembertForMultipleChoice,
        CamembertForQuestionAnswering,
        CamembertForSequenceClassification,
        CamembertForTokenClassification,
        CamembertModel,
        CamembertPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_camembert import (
        TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFCamembertForCausalLM,
        TFCamembertForMaskedLM,
        TFCamembertForMultipleChoice,
        TFCamembertForQuestionAnswering,
        TFCamembertForSequenceClassification,
        TFCamembertForTokenClassification,
        TFCamembertModel,
        TFCamembertPreTrainedModel,
    )

else:
  import sys

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











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__     (						_UpperCamelCase     :	Optional[Any]							):
   return EnvironmentCommand()





class 	__lowerCAmelCase       (		lowerCAmelCase__				):




 @staticmethod
 def     lowerCamelCase (  __UpperCAmelCase			):



    '''simple docstring'''
    __lowerCamelCase  							=      parser.add_parser('''env'''		,			help='''Print relevant system environment info.'''			)
    download_parser.set_defaults(func=__UpperCAmelCase			)




 def     lowerCamelCase (  self			):



    '''simple docstring'''
    __lowerCamelCase  							=      {
        '''`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     lowerCamelCase (  __UpperCAmelCase			):



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






