

"""simple docstring"""




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[Any]	  =			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_     :			Union[str, Any]	  =			{
    '''facebook/xmod-base''': '''https://huggingface.co/facebook/xmod-base/resolve/main/config.json''',
    '''facebook/xmod-large-prenorm''': '''https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json''',
    '''facebook/xmod-base-13-125k''': '''https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-125k''': '''https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-195k''': '''https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json''',
    '''facebook/xmod-base-60-125k''': '''https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json''',
    '''facebook/xmod-base-60-265k''': '''https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json''',
    '''facebook/xmod-base-75-125k''': '''https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json''',
    '''facebook/xmod-base-75-269k''': '''https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json''',
}


class 		_A       (			__a					):
      __a								=	'xmod'





      def __init__(  self    ,						SCREAMING_SNAKE_CASE__=30522    ,						SCREAMING_SNAKE_CASE__=768    ,						SCREAMING_SNAKE_CASE__=12    ,						SCREAMING_SNAKE_CASE__=12    ,						SCREAMING_SNAKE_CASE__=3072    ,						SCREAMING_SNAKE_CASE__="gelu"    ,						SCREAMING_SNAKE_CASE__=0.1    ,						SCREAMING_SNAKE_CASE__=0.1    ,						SCREAMING_SNAKE_CASE__=512    ,						SCREAMING_SNAKE_CASE__=2    ,						SCREAMING_SNAKE_CASE__=0.02    ,						SCREAMING_SNAKE_CASE__=1e-12    ,						SCREAMING_SNAKE_CASE__=1    ,						SCREAMING_SNAKE_CASE__=0    ,						SCREAMING_SNAKE_CASE__=2    ,						SCREAMING_SNAKE_CASE__="absolute"    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__=None    ,						SCREAMING_SNAKE_CASE__=False    ,						SCREAMING_SNAKE_CASE__=2    ,						SCREAMING_SNAKE_CASE__=False    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__=("en_XX",)    ,						SCREAMING_SNAKE_CASE__=None    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					Tuple:
         super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__    ,						bos_token_id=SCREAMING_SNAKE_CASE__    ,						eos_token_id=SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)

         lowerCamelCase__						=			vocab_size
         lowerCamelCase__						=			hidden_size
         lowerCamelCase__						=			num_hidden_layers
         lowerCamelCase__						=			num_attention_heads
         lowerCamelCase__						=			hidden_act
         lowerCamelCase__						=			intermediate_size
         lowerCamelCase__						=			hidden_dropout_prob
         lowerCamelCase__						=			attention_probs_dropout_prob
         lowerCamelCase__						=			max_position_embeddings
         lowerCamelCase__						=			type_vocab_size
         lowerCamelCase__						=			initializer_range
         lowerCamelCase__						=			layer_norm_eps
         lowerCamelCase__						=			position_embedding_type
         lowerCamelCase__						=			use_cache
         lowerCamelCase__						=			classifier_dropout
         lowerCamelCase__						=			pre_norm
         lowerCamelCase__						=			adapter_reduction_factor
         lowerCamelCase__						=			adapter_layer_norm
         lowerCamelCase__						=			adapter_reuse_layer_norm
         lowerCamelCase__						=			ln_before_adapter
         lowerCamelCase__						=			list(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			default_language






class 		_A       (			__a					):





      @property
      def 					_lowerCamelCase  (  self		)   ->					Mapping[str, Mapping[int, str]]:
         if self.task == "multiple-choice":
            lowerCamelCase__						=			{0: "batch", 1: "choice", 2: "sequence"}
         else:
            lowerCamelCase__						=			{0: "batch", 1: "sequence"}
         return OrderedDict(
             [
                 ("input_ids", dynamic_axis),
                 ("attention_mask", dynamic_axis),
             ]		)







"""simple docstring"""




# Algorithm for the pigeonhole sorting





def 	UpperCAmelCase__   (				A__   )      ->      Dict:




   """simple docstring"""
   lowerCamelCase__						=			min(A__   )  # min() finds the minimum value
   lowerCamelCase__						=			max(A__   )  # max() finds the maximum value

   lowerCamelCase__						=			max_val - min_val + 1  # size is difference of max and min values plus one

   # list of pigeonholes of size equal to the variable size
   lowerCamelCase__						=			[0] * size

   # Populate the pigeonholes.
   for x in a:
      assert isinstance(A__	,    A__   ), "integers only please"
      holes[x - min_val] += 1

   # Putting the elements back into the array in an order.
   lowerCamelCase__						=			0
   for count in range(A__   ):
      while holes[count] > 0:
         holes[count] -= 1
         lowerCamelCase__						=			count + min_val
         i += 1



def 	UpperCAmelCase__   (				)      ->      Optional[int]:




   """simple docstring"""
   lowerCamelCase__						=			[8, 3, 2, 7, 4, 6, 8]
   pigeonhole_sort(A__   )
   print("Sorted order is:"	,    " ".join(A__   )   )


if __name__ == "__main__":
     main()




