from collections import OrderedDict
from typing import Mapping

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


snake_case__				= logging.get_logger(__name__)

snake_case__				= {
    '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  UpperCamelCase				( _snake_case ):

     '''simple docstring'''

     A_										=  'roformer'



     def __init__(					self				,				A_=5_00_00				,				A_=None				,				A_=7_68				,				A_=12				,				A_=12				,				A_=30_72				,				A_="gelu"				,				A_=0.1				,				A_=0.1				,				A_=15_36				,				A_=2				,				A_=0.02				,				A_=1E-1_2				,				A_=0				,				A_=False				,				A_=True				,				**A_				,				) ->				Dict:






           """simple docstring"""
           super().__init__(pad_token_id=lowerCAmelCase__				,				**lowerCAmelCase__						)

           _lowerCamelCase			    =				vocab_size
           _lowerCamelCase			    =				hidden_size if embedding_size is None else embedding_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			    =				rotary_value
           _lowerCamelCase			    =				use_cache





class  UpperCamelCase				( _snake_case ):

     '''simple docstring'''

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






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


def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase		)						->    str:



      '''simple docstring'''

      _lowerCamelCase			    =				0
      while b > 0:
            if b & 1:
                  res += a

            a += a
            b >>= 1

      return res
def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase		)						->    Optional[Any]:



      '''simple docstring'''

      _lowerCamelCase			    =				0
      while b > 0:
            if b & 1:
                  _lowerCamelCase			    =				((res % c) + (a % c)) % c

            a += a
            b >>= 1

      return res