

def    _lowercase			(	a__						:			Optional[int]							,  a__						:			Optional[Any]							,  a__						:			List[Any]							,  a__						:			Optional[int]							,  a__						:			Dict							,  a__						:			Dict					)							->					List[str]:





	"""simple docstring"""


	if index == r:
		for j in range(snake_case__					):
			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			=   arr[i]
	combination_util(snake_case__							,  snake_case__							,  snake_case__							,  index + 1							,  snake_case__							,  i + 1					)
	# current is excluded, replace it with
	# next (Note that i+1 is passed, but
	# index is not changed)
	combination_util(snake_case__							,  snake_case__							,  snake_case__							,  snake_case__							,  snake_case__							,  i + 1					)
	# The main function that prints all combinations
	# of size r in arr[] of size n. This function
	# mainly uses combinationUtil()



def    _lowercase			(	a__						:			int							,  a__						:			List[str]							,  a__						:			List[Any]					)							->					Optional[Any]:





	"""simple docstring"""


	_UpperCamelCase			=   [0] * r
	# Print all combination using temporary array 'data[]'
	combination_util(snake_case__							,  snake_case__							,  snake_case__							,  0							,  snake_case__							,  0					)


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








from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__					:     Optional[int]       =     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__					:     List[str]       =     {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}


class 		_SCREAMING_SNAKE_CASE     (						A     ):
     __SCREAMING_SNAKE_CASE     					=    '''camembert'''


     def __init__(  self							,					A_=3_05_22							,					A_=7_68							,					A_=12							,					A_=12							,					A_=30_72							,					A_="gelu"							,					A_=0.1							,					A_=0.1							,					A_=5_12							,					A_=2							,					A_=0.0_2							,					A_=1e-12							,					A_=1							,					A_=0							,					A_=2							,					A_="absolute"							,					A_=True							,					A_=None							,					**A_							,					):
       super().__init__(pad_token_id=A_							,					bos_token_id=A_							,					eos_token_id=A_							,					**A_    )

       _UpperCAmelCase		:							Optional[Any]							=     vocab_size
       _UpperCAmelCase		:							int							=     hidden_size
       _UpperCAmelCase		:							Any							=     num_hidden_layers
       _UpperCAmelCase		:							Optional[Any]							=     num_attention_heads
       _UpperCAmelCase		:							Dict							=     hidden_act
       _UpperCAmelCase		:							str							=     intermediate_size
       _UpperCAmelCase		:							str							=     hidden_dropout_prob
       _UpperCAmelCase		:							List[Any]							=     attention_probs_dropout_prob
       _UpperCAmelCase		:							List[Any]							=     max_position_embeddings
       _UpperCAmelCase		:							Union[str, Any]							=     type_vocab_size
       _UpperCAmelCase		:							List[Any]							=     initializer_range
       _UpperCAmelCase		:							Optional[Any]							=     layer_norm_eps
       _UpperCAmelCase		:							int							=     position_embedding_type
       _UpperCAmelCase		:							Tuple							=     use_cache
       _UpperCAmelCase		:							Any							=     classifier_dropout


class 		_SCREAMING_SNAKE_CASE     (						A     ):


     @property
     def        __snake_case(  self    ):
       if self.task == "multiple-choice":
         _UpperCAmelCase		:							Any							=     {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
         _UpperCAmelCase		:							List[Any]							=     {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]    )





