from pathlib import Path

from .config_args import default_config_file, load_config_from_file
from .config_utils import SubcommandHelpFormatter


UpperCAmelCase     						=			'''Update an existing config file with the latest defaults while maintaining the old configuration.'''


def SCREAMING_SNAKE_CASE			(       lowercase_:		Tuple			):
       _UpperCamelCase       :    int					  =					args.config_file
       if config_file is None and Path(_lowerCamelCase			).exists():
              _UpperCamelCase       :    Tuple					  =					default_config_file
       elif not Path(_lowerCamelCase			).exists():
              raise ValueError(F"The passed config file located at {config_file} doesn\'t exist."			)
       _UpperCamelCase       :    Any					  =					load_config_from_file(_lowerCamelCase			)

       if config_file.endswith('.json'			):
              config.to_json_file(_lowerCamelCase			)
       else:
              config.to_yaml_file(_lowerCamelCase			)
       return config_file


def SCREAMING_SNAKE_CASE			(       lowercase_:		Tuple						,  lowercase_:		Dict			):
       _UpperCamelCase       :    int					  =					parser.add_parser('update'						,  parents=_lowerCamelCase						,  help=_lowerCamelCase						,  formatter_class=_lowerCamelCase			)
       parser.add_argument(
           '--config_file'						,  default=_lowerCamelCase						,  help=(
               'The path to the config file to update. Will default to a file named default_config.yaml in the cache '
               'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
               'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
               'with \'huggingface\'.'
           )						,  )

       parser.set_defaults(func=_lowerCamelCase			)
       return parser





def SCREAMING_SNAKE_CASE			(       lowercase_:		Any			):
       _UpperCamelCase       :    Optional[Any]					  =					update_config(_lowerCamelCase			)
       print(F"Sucessfully updated the configuration file at {config_file}."			)




from typing import TYPE_CHECKING

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


UpperCAmelCase     						=			{
    '''configuration_mpnet''': ['''MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MPNetConfig'''],
    '''tokenization_mpnet''': ['''MPNetTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase     						=			['''MPNetTokenizerFast''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase     						=			[
     '''MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''MPNetForMaskedLM''',
     '''MPNetForMultipleChoice''',
     '''MPNetForQuestionAnswering''',
     '''MPNetForSequenceClassification''',
     '''MPNetForTokenClassification''',
     '''MPNetLayer''',
     '''MPNetModel''',
     '''MPNetPreTrainedModel''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase     						=			[
     '''TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFMPNetEmbeddings''',
     '''TFMPNetForMaskedLM''',
     '''TFMPNetForMultipleChoice''',
     '''TFMPNetForQuestionAnswering''',
     '''TFMPNetForSequenceClassification''',
     '''TFMPNetForTokenClassification''',
     '''TFMPNetMainLayer''',
     '''TFMPNetModel''',
     '''TFMPNetPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
 from .tokenization_mpnet import MPNetTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_mpnet_fast import MPNetTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mpnet import (
      MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
      MPNetForMaskedLM,
      MPNetForMultipleChoice,
      MPNetForQuestionAnswering,
      MPNetForSequenceClassification,
      MPNetForTokenClassification,
      MPNetLayer,
      MPNetModel,
      MPNetPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_mpnet import (
      TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFMPNetEmbeddings,
      TFMPNetForMaskedLM,
      TFMPNetForMultipleChoice,
      TFMPNetForQuestionAnswering,
      TFMPNetForSequenceClassification,
      TFMPNetForTokenClassification,
      TFMPNetMainLayer,
      TFMPNetModel,
      TFMPNetPreTrainedModel,
  )

else:
 import sys

 UpperCAmelCase     						=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



