



"""simple docstring"""
def       _snake_case						(						UpperCamelCase						:		int			,		UpperCamelCase						:		List[str]			,		UpperCamelCase						:		Optional[Any]			,		UpperCamelCase						:		Tuple			,		UpperCamelCase						:		List[Any]			,		UpperCamelCase						:		str						):
 if index == r:
  for j in range(_a						):
   print(data[j]			,		end=""" """						)
  print(""" """						)
  return
 #  When no more elements are there to put in data[]
 if i >= n:
  return
 # current is included, put next at next location
 UpperCAmelCase	:					str	=	arr[i]
 combination_util(_a			,		_a			,		_a			,		index + 1			,		_a			,		i + 1						)
 # current is excluded, replace it with
 # next (Note that i+1 is passed, but
 # index is not changed)
 combination_util(_a			,		_a			,		_a			,		_a			,		_a			,		i + 1						)
 # The main function that prints all combinations
 # of size r in arr[] of size n. This function
 # mainly uses combinationUtil()

def       _snake_case						(						UpperCamelCase						:		Optional[int]			,		UpperCamelCase						:		List[str]			,		UpperCamelCase						:		Tuple						):
 # A temporary array to store all combination one by one
 UpperCAmelCase	:					Any	=	[0] * r
 # Print all combination using temporary array 'data[]'
 combination_util(_a			,		_a			,		_a			,		0			,		_a			,		0						)


if __name__ == "__main__":
      # Driver code to check the function above
      A:   Union[str, Any]								=		[1_0, 2_0, 3_0, 4_0, 5_0]
      print_combination(arr, len(arr), 3)
      # This code is contributed by Ambuj sahu





"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase__    :  List[Any]							    =	{
    '''configuration_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__    :  Any							    =	['''DistilBertTokenizerFast''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__    :  int							    =	[
         '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''DistilBertForMaskedLM''',
         '''DistilBertForMultipleChoice''',
         '''DistilBertForQuestionAnswering''',
         '''DistilBertForSequenceClassification''',
         '''DistilBertForTokenClassification''',
         '''DistilBertModel''',
         '''DistilBertPreTrainedModel''',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__    :  Dict							    =	[
         '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFDistilBertForMaskedLM''',
         '''TFDistilBertForMultipleChoice''',
         '''TFDistilBertForQuestionAnswering''',
         '''TFDistilBertForSequenceClassification''',
         '''TFDistilBertForTokenClassification''',
         '''TFDistilBertMainLayer''',
         '''TFDistilBertModel''',
         '''TFDistilBertPreTrainedModel''',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__    :  Tuple							    =	[
         '''FlaxDistilBertForMaskedLM''',
         '''FlaxDistilBertForMultipleChoice''',
         '''FlaxDistilBertForQuestionAnswering''',
         '''FlaxDistilBertForSequenceClassification''',
         '''FlaxDistilBertForTokenClassification''',
         '''FlaxDistilBertModel''',
         '''FlaxDistilBertPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_distilbert import (
         DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
         DistilBertConfig,
         DistilBertOnnxConfig,
     )
     from .tokenization_distilbert import DistilBertTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_distilbert_fast import DistilBertTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_distilbert import (
              DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              DistilBertForMaskedLM,
              DistilBertForMultipleChoice,
              DistilBertForQuestionAnswering,
              DistilBertForSequenceClassification,
              DistilBertForTokenClassification,
              DistilBertModel,
              DistilBertPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_distilbert import (
              TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFDistilBertForMaskedLM,
              TFDistilBertForMultipleChoice,
              TFDistilBertForQuestionAnswering,
              TFDistilBertForSequenceClassification,
              TFDistilBertForTokenClassification,
              TFDistilBertMainLayer,
              TFDistilBertModel,
              TFDistilBertPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_distilbert import (
              FlaxDistilBertForMaskedLM,
              FlaxDistilBertForMultipleChoice,
              FlaxDistilBertForQuestionAnswering,
              FlaxDistilBertForSequenceClassification,
              FlaxDistilBertForTokenClassification,
              FlaxDistilBertModel,
              FlaxDistilBertPreTrainedModel,
          )

else:
     import sys

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





