



A__						:						List[Any]          =      [0.3_3, 0.4_4, 0.5_5, 0.4_4, 0.3_3]
A__						:						str          =      3
A__						:						str          =      5

# Buffer Space (with Parameters Space)
A__						:						list[float]          =      []
A__						:						list[float]          =      []

# Machine Time
A__						:						List[str]          =      0


def     UpperCamelCase(						__UpperCamelCase							:	str				):
  global buffer_space, params_space, machine_time, K, m, t

  # Choosing Dynamical Systems (All)
  for key, value in enumerate(__UpperCamelCase				):
    # Evolution Parameter
    lowerCAmelCase_    :  Optional[int]             =				float(seed / value				)

    # Control Theory: Orbit Change
    lowerCAmelCase_    :  str             =				(buffer_space[(key + 1) % m] + e) % 1

    # Control Theory: Trajectory Change
    lowerCAmelCase_    :  List[Any]             =				(params_space[key] + e) % 1 + 3

    # Modification (Transition Function) - Jumps
    lowerCAmelCase_    :  Tuple             =				round(float(r * value * (1 - value)				)  ,10				)
    lowerCAmelCase_    :  Optional[int]             =				r  # Saving to Parameters Space

  # Logistic Map
  assert max(__UpperCamelCase				) < 1
  assert max(__UpperCamelCase				) < 4

  # Machine Time
  machine_time += 1


def     UpperCamelCase(						):
  global buffer_space, params_space, machine_time, K, m, t

  # PRNG (Xorshift by George Marsaglia)
  def xorshift(__UpperCamelCase							:	str  ,__UpperCamelCase							:	List[Any]				):
    x ^= y >> 13
    y ^= x << 17
    x ^= y >> 5
    return x

  # Choosing Dynamical Systems (Increment)
  lowerCAmelCase_    :  List[Any]             =				machine_time % m

  # Evolution (Time Length)
  for _ in range(0  ,__UpperCamelCase				):
    # Variables (Position + Parameters)
    lowerCAmelCase_    :  Tuple             =				params_space[key]
    lowerCAmelCase_    :  Tuple             =				buffer_space[key]

    # Modification (Transition Function) - Flow
    lowerCAmelCase_    :  Tuple             =				round(float(r * value * (1 - value)				)  ,10				)
    lowerCAmelCase_    :  int             =				(machine_time * 0.0_1 + r * 1.0_1) % 1 + 3

  # Choosing Chaotic Data
  lowerCAmelCase_    :  Dict             =				int(buffer_space[(key + 2) % m] * (10**10)				)
  lowerCAmelCase_    :  Any             =				int(buffer_space[(key - 2) % m] * (10**10)				)

  # Machine Time
  machine_time += 1

  return xorshift(__UpperCamelCase  ,__UpperCamelCase				) % 0Xffff_ffff


def     UpperCamelCase(						):
  global buffer_space, params_space, machine_time, K, m, t

  lowerCAmelCase_    :  int             =				K
  lowerCAmelCase_    :  List[Any]             =				[0] * m
  lowerCAmelCase_    :  Any             =				0


if __name__ == "__main__":
      # Initialization
      reset()

      # Pushing Data (Input)
      import random

      A__						:						Optional[int]          =      random.sample(range(0XFFFF_FFFF), 100)
      for chunk in message:
            push(chunk)

      # for controlling
      A__						:						Any          =      ''''''

      # Pulling Data (Output)
      while inp in ("e", "E"):
            print(F'''{format(pull(), "#04x")}''')
            print(buffer_space)
            print(params_space)
            A__						:						int          =      input('''(e)exit? ''').strip()










from collections import OrderedDict
from typing import Mapping

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


A__						:						Dict          =      logging.get_logger(__name__)

A__						:						List[str]          =      {
    '''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        __snake_case		(  UpperCamelCase_		):
							_a       =				'''electra'''




							def __init__( self  : Dict       ,       A_  : Dict=3_0_5_2_2       ,       A_  : List[Any]=1_2_8       ,       A_  : Dict=2_5_6       ,       A_  : Any=1_2       ,       A_  : Optional[Any]=4       ,       A_  : Optional[int]=1_0_2_4       ,       A_  : Optional[int]="gelu"       ,       A_  : str=0.1       ,       A_  : Optional[int]=0.1       ,       A_  : str=5_1_2       ,       A_  : Optional[int]=2       ,       A_  : Dict=0.02       ,       A_  : Union[str, Any]=1e-12       ,       A_  : List[Any]="first"       ,       A_  : List[str]=True       ,       A_  : List[str]="gelu"       ,       A_  : Any=0.1       ,       A_  : int=0       ,       A_  : Optional[Any]="absolute"       ,       A_  : Optional[int]=True       ,       A_  : str=None       ,       **A_  : List[Any]       ,       ):
									super().__init__(pad_token_id=A_       ,       **A_)

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

									lowerCAmelCase_    :  Union[str, Any]             =				summary_type
									lowerCAmelCase_    :  str             =				summary_use_proj
									lowerCAmelCase_    :  str             =				summary_activation
									lowerCAmelCase_    :  List[Any]             =				summary_last_dropout
									lowerCAmelCase_    :  Optional[Any]             =				position_embedding_type
									lowerCAmelCase_    :  List[Any]             =				use_cache
									lowerCAmelCase_    :  Any             =				classifier_dropout





class        __snake_case		(  UpperCamelCase_		):




							@property
							def      UpperCAmelCase__    ( self  : Union[str, Any]):
									if self.task == "multiple-choice":
											lowerCAmelCase_    :  Any             =				{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
									else:
											lowerCAmelCase_    :  Union[str, Any]             =				{0: '''batch''', 1: '''sequence'''}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									        ('''token_type_ids''', dynamic_axis),
									    ])





