'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

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


_A		:      str						   =logging.get_logger(__name__)

_A		:      int						   ={
    '''google/electra-small-generator''': '''https://huggingface.co/google/electra-small-generator/resolve/main/config.json''',
    '''google/electra-base-generator''': '''https://huggingface.co/google/electra-base-generator/resolve/main/config.json''',
    '''google/electra-large-generator''': '''https://huggingface.co/google/electra-large-generator/resolve/main/config.json''',
    '''google/electra-small-discriminator''': (
        '''https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-base-discriminator''': (
        '''https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-large-discriminator''': (
        '''https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'''
    ),
}




class _lowerCAmelCase			(	snake_case					):
      UpperCAmelCase_	:						Optional[int]	 =       "electra"







      def __init__(  self  ,    lowercase=3_0522  ,    lowercase=128  ,    lowercase=256  ,    lowercase=12  ,    lowercase=4  ,    lowercase=1024  ,    lowercase="gelu"  ,    lowercase=0.1  ,    lowercase=0.1  ,    lowercase=512  ,    lowercase=2  ,    lowercase=0.02  ,    lowercase=1e-12  ,    lowercase="first"  ,    lowercase=True  ,    lowercase="gelu"  ,    lowercase=0.1  ,    lowercase=0  ,    lowercase="absolute"  ,    lowercase=True  ,    lowercase=None  ,    **lowercase  ,    ):
        super().__init__(pad_token_id=lowercase  ,    **lowercase     )

        lowercase				:							Dict									=   vocab_size
        lowercase				:							Optional[int]									=   embedding_size
        lowercase				:							Optional[int]									=   hidden_size
        lowercase				:							str									=   num_hidden_layers
        lowercase				:							List[str]									=   num_attention_heads
        lowercase				:							Optional[int]									=   intermediate_size
        lowercase				:							str									=   hidden_act
        lowercase				:							List[Any]									=   hidden_dropout_prob
        lowercase				:							Any									=   attention_probs_dropout_prob
        lowercase				:							List[str]									=   max_position_embeddings
        lowercase				:							str									=   type_vocab_size
        lowercase				:							Optional[int]									=   initializer_range
        lowercase				:							Tuple									=   layer_norm_eps

        lowercase				:							Tuple									=   summary_type
        lowercase				:							List[Any]									=   summary_use_proj
        lowercase				:							str									=   summary_activation
        lowercase				:							Tuple									=   summary_last_dropout
        lowercase				:							List[Any]									=   position_embedding_type
        lowercase				:							List[Any]									=   use_cache
        lowercase				:							int									=   classifier_dropout





class _lowerCAmelCase			(	snake_case					):







      @property
      def      lowerCamelCase__      (  self     ):
        if self.task == "multiple-choice":
          lowercase				:							Dict									=   {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
        else:
          lowercase				:							Optional[int]									=   {0: '''batch''', 1: '''sequence'''}
        return OrderedDict(
            [
                ('''input_ids''', dynamic_axis),
                ('''attention_mask''', dynamic_axis),
                ('''token_type_ids''', dynamic_axis),
            ]     )
'''simple docstring'''
from __future__ import annotations

import math
import random







def 				__UpperCamelCase (					__UpperCAmelCase  :					int ,   __UpperCAmelCase  :					int ,   __UpperCAmelCase  :					int			)							->	list[int]:
  lowercase				:							Union[str, Any]									=   d * e - 1
  lowercase				:							List[str]									=   0
  lowercase				:							Tuple									=   0
  while p == 0:
    lowercase				:							Optional[Any]									=   random.randint(2 ,   n - 1			)
    lowercase				:							Dict									=   k
    while True:
      if t % 2 == 0:
        lowercase				:							List[Any]									=   t // 2
        lowercase				:							Union[str, Any]									=   (g**t) % n
        lowercase				:							Optional[Any]									=   math.gcd(x - 1 ,   __UpperCAmelCase			)
        if x > 1 and y > 1:
          lowercase				:							Dict									=   y
          lowercase				:							Any									=   n // y
          break  # find the correct factors
      else:
        break  # t is not divisible by 2, break and choose another g
  return sorted([p, q]			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()