



import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


A__						:						str          =      TypeVar('''T''', bound='''TaskTemplate''')



@dataclass(frozen=a__		)
class        __snake_case		(  abc.ABC		):
       # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
       _a       =				42
       _a       =				42
       _a       =				42




       def      UpperCAmelCase__    ( self  : int       ,       A_  : Tuple):
         return copy.deepcopy(self)




       @property
       def      UpperCAmelCase__    ( self  : Dict):
         return Features(**self.input_schema       ,       **self.label_schema)




       @property
       @abc.abstractmethod
       def      UpperCAmelCase__    ( self  : List[Any]):
         raise NotImplementedError







       @classmethod
       def      UpperCAmelCase__    ( cls  : Union[str, Any]       ,       A_  : int):
         lowerCAmelCase_    :  Any             =				{f.name for f in dataclasses.fields(cls)}
         return cls(**{k: v for k, v in template_dict.items() if k in field_names})










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),
									    ])





