



from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase						=       logging.get_logger(__name__)

__lowerCamelCase						=       {
    """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json""",
    """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json""",
    """junnyu/roformer_chinese_char_small""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json"""
    ),
    """junnyu/roformer_chinese_char_base""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_discriminator""": (
        """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_generator""": (
        """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json"""
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}



class 		_snake_case   (      lowerCamelCase					):





 """simple docstring"""



 lowerCamelCase_        =      '''roformer'''
 def __init__(    self						,     a=5_0_0_0_0						,     a=None						,     a=7_6_8						,     a=1_2						,     a=1_2						,     a=3_0_7_2						,     a="gelu"						,     a=0.1						,     a=0.1						,     a=1_5_3_6						,     a=2						,     a=0.02						,     a=1e-12						,     a=0						,     a=False						,     a=True						,     **a						,     )						->				Dict:




   """simple docstring"""







   super().__init__(pad_token_id=A_						,     **A_       )

   _A							     =     vocab_size
   _A							     =     hidden_size if embedding_size is None else embedding_size
   _A							     =     hidden_size
   _A							     =     num_hidden_layers
   _A							     =     num_attention_heads
   _A							     =     hidden_act
   _A							     =     intermediate_size
   _A							     =     hidden_dropout_prob
   _A							     =     attention_probs_dropout_prob
   _A							     =     max_position_embeddings
   _A							     =     type_vocab_size
   _A							     =     initializer_range
   _A							     =     layer_norm_eps
   _A							     =     rotary_value
   _A							     =     use_cache







class 		_snake_case   (      lowerCamelCase					):





 """simple docstring"""



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




   """simple docstring"""







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






from math import factorial






def 				_UpperCAmelCase			(    A = 20     ):




   '''simple docstring'''

   UpperCAmelCase__						=2 * n  # middle entry of odd rows starting at row 3 is the solution for n = 1,
   # 2, 3,...
   UpperCAmelCase__						=n // 2

   return int(factorial(A     ) / (factorial(A     ) * factorial(n - k     ))     )


if __name__ == "__main__":
    import sys

    if len(sys.argv) == 1:
        print(solution(20))
    else:
        try:
            UpperCamelCase_												=	int(sys.argv[1])
            print(solution(n))
        except ValueError:
            print('Invalid entry - please enter a number.')



