






"""simple docstring"""







def       _lowerCAmelCase       (      lowerCAmelCase		):







       '''simple docstring'''
       assert (
           isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_		) and number_of_steps > 0
       ), F'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
       if number_of_steps == 1:
              return 1
       UpperCAmelCase	    =			1, 1
       for _ in range(number_of_steps - 1		):
              UpperCAmelCase	    =			current + previous, current
       return current


if __name__ == "__main__":
 import doctest

 doctest.testmod()








"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase_	:    Tuple            =      logging.get_logger(__name__)

lowerCAmelCase_	:    List[str]            =      {
    '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json''',
    '''google/bigbird-roberta-large''': '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json''',
    '''google/bigbird-base-trivia-itc''': '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json''',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}





class   UpperCamelCase_ (       a_  ):
  _A       :					Any				=	'big_bird'



  def __init__(      self ,		snake_case__=5_03_58 ,		snake_case__=7_68 ,		snake_case__=12 ,		snake_case__=12 ,		snake_case__=30_72 ,		snake_case__="gelu_new" ,		snake_case__=0.1 ,		snake_case__=0.1 ,		snake_case__=40_96 ,		snake_case__=2 ,		snake_case__=0.02 ,		snake_case__=1e-12 ,		snake_case__=True ,		snake_case__=0 ,		snake_case__=1 ,		snake_case__=2 ,		snake_case__=66 ,		snake_case__="block_sparse" ,		snake_case__=True ,		snake_case__=False ,		snake_case__=64 ,		snake_case__=3 ,		snake_case__=None ,		**snake_case__ ,		)			->			List[str]:



         """simple docstring"""





         super().__init__(
             pad_token_id=snake_case__ ,		bos_token_id=snake_case__ ,		eos_token_id=snake_case__ ,		sep_token_id=snake_case__ ,		**snake_case__ ,		)

         UpperCAmelCase	    =			vocab_size
         UpperCAmelCase	    =			max_position_embeddings
         UpperCAmelCase	    =			hidden_size
         UpperCAmelCase	    =			num_hidden_layers
         UpperCAmelCase	    =			num_attention_heads
         UpperCAmelCase	    =			intermediate_size
         UpperCAmelCase	    =			hidden_act
         UpperCAmelCase	    =			hidden_dropout_prob
         UpperCAmelCase	    =			attention_probs_dropout_prob
         UpperCAmelCase	    =			initializer_range
         UpperCAmelCase	    =			type_vocab_size
         UpperCAmelCase	    =			layer_norm_eps
         UpperCAmelCase	    =			use_cache

         UpperCAmelCase	    =			rescale_embeddings
         UpperCAmelCase	    =			attention_type
         UpperCAmelCase	    =			use_bias
         UpperCAmelCase	    =			block_size
         UpperCAmelCase	    =			num_random_blocks
         UpperCAmelCase	    =			classifier_dropout





class   UpperCamelCase_ (       a_  ):



  @property
  def 		UpperCamelCase_				(      self				)			->			Mapping[str, Mapping[int, str]]:



         """simple docstring"""





         if self.task == "multiple-choice":
                UpperCAmelCase	    =			{0: """batch""", 1: """choice""", 2: """sequence"""}
         else:
                UpperCAmelCase	    =			{0: """batch""", 1: """sequence"""}
         return OrderedDict(
             [
                 ("""input_ids""", dynamic_axis),
                 ("""attention_mask""", dynamic_axis),
             ]				)
