






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

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


A_			: List[Any]				=			logging.get_logger(__name__)

A_			: Any				=			{
    "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 		a_      (	snake_case_ ):







      '''simple docstring'''

      lowerCamelCase__       :				List[str] =	'electra'




      def __init__(self,     lowerCamelCase_=3_0_5_2_2,     lowerCamelCase_=1_2_8,     lowerCamelCase_=2_5_6,     lowerCamelCase_=1_2,     lowerCamelCase_=4,     lowerCamelCase_=1_0_2_4,     lowerCamelCase_="gelu",     lowerCamelCase_=0.1,     lowerCamelCase_=0.1,     lowerCamelCase_=5_1_2,     lowerCamelCase_=2,     lowerCamelCase_=0.02,     lowerCamelCase_=1e-12,     lowerCamelCase_="first",     lowerCamelCase_=True,     lowerCamelCase_="gelu",     lowerCamelCase_=0.1,     lowerCamelCase_=0,     lowerCamelCase_="absolute",     lowerCamelCase_=True,     lowerCamelCase_=None,     **lowerCamelCase_,     ):

       '''simple docstring'''



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

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

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



class 		a_      (	snake_case_ ):







      '''simple docstring'''

      @property
      def 			a__							(self					):

       '''simple docstring'''



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




"""simple docstring"""




import doctest

import projectq
from projectq.ops import H, Measure
def    __SCREAMING_SNAKE_CASE						(						lowercase__      ):
					"""simple docstring"""
					A			=					quantum_engine.allocate_qubit()
					H | qubit
					Measure | qubit
					return int(lowercase__      )


if __name__ == "__main__":
	doctest.testmod()

	# initialises a new quantum backend
	__A     :    Dict    =		projectq.MainEngine()

	# Generate a list of 10 random numbers
	__A     :    Any    =		[get_random_number(quantum_engine) for _ in range(10)]

	# Flushes the quantum engine from memory
	quantum_engine.flush()

	print('Random numbers', random_numbers_list)





