'''simple docstring'''


from typing import List, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

snake_case__	:     int      =    {
    '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
    # See all LED models at https://huggingface.co/models?filter=led
}






class 	__SCREAMING_SNAKE_CASE		(			lowerCamelCase_			):







  '''simple docstring'''






  lowerCamelCase_						:Optional[int]		       =						'''led'''
  lowerCamelCase_						:List[str]		       =						{
      '''num_attention_heads''': '''encoder_attention_heads''',
      '''hidden_size''': '''d_model''',
      '''attention_probs_dropout_prob''': '''attention_dropout''',
      '''initializer_range''': '''init_std''',
  }


  def __init__(					self ,						snake_case_=5_0_2_6_5 ,						snake_case_=1_6_3_8_4 ,						snake_case_=1_0_2_4 ,						snake_case_=1_2 ,						snake_case_=4_0_9_6 ,						snake_case_=1_6 ,						snake_case_=1_2 ,						snake_case_=4_0_9_6 ,						snake_case_=1_6 ,						snake_case_=0.0 ,						snake_case_=0.0 ,						snake_case_=True ,						snake_case_=True ,						snake_case_="gelu" ,						snake_case_=1_0_2_4 ,						snake_case_=0.1 ,						snake_case_=0.0 ,						snake_case_=0.0 ,						snake_case_=0.02 ,						snake_case_=2 ,						snake_case_=0.0 ,						snake_case_=1 ,						snake_case_=0 ,						snake_case_=2 ,						snake_case_ = 5_1_2 ,						**snake_case_ ,						):




       '''simple docstring'''

       UpperCAmelCase_				:  Dict  = vocab_size
       UpperCAmelCase_				:  Union[str, Any]  = max_encoder_position_embeddings
       UpperCAmelCase_				:  int  = max_decoder_position_embeddings
       UpperCAmelCase_				:  int  = d_model
       UpperCAmelCase_				:  Optional[Any]  = encoder_ffn_dim
       UpperCAmelCase_				:  Any  = encoder_layers
       UpperCAmelCase_				:  Dict  = encoder_attention_heads
       UpperCAmelCase_				:  List[Any]  = decoder_ffn_dim
       UpperCAmelCase_				:  Optional[Any]  = decoder_layers
       UpperCAmelCase_				:  Union[str, Any]  = decoder_attention_heads
       UpperCAmelCase_				:  int  = dropout
       UpperCAmelCase_				:  str  = attention_dropout
       UpperCAmelCase_				:  List[str]  = activation_dropout
       UpperCAmelCase_				:  Any  = activation_function
       UpperCAmelCase_				:  Any  = init_std
       UpperCAmelCase_				:  str  = encoder_layerdrop
       UpperCAmelCase_				:  List[str]  = decoder_layerdrop
       UpperCAmelCase_				:  Dict  = classifier_dropout
       UpperCAmelCase_				:  Optional[Any]  = use_cache
       UpperCAmelCase_				:  Union[str, Any]  = encoder_layers
       UpperCAmelCase_				:  Dict  = attention_window

       super().__init__(
           pad_token_id=snake_case_ ,						bos_token_id=snake_case_ ,						eos_token_id=snake_case_ ,						is_encoder_decoder=snake_case_ ,						decoder_start_token_id=snake_case_ ,						**snake_case_ ,						)









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	:   Tuple	=					{
    '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 			_SCREAMING_SNAKE_CASE      (  lowerCAmelCase__):
						_UpperCamelCase:Tuple	=		"electra"







						def __init__(			self     ,						_SCREAMING_SNAKE_CASE=3_0522     ,						_SCREAMING_SNAKE_CASE=128     ,						_SCREAMING_SNAKE_CASE=256     ,						_SCREAMING_SNAKE_CASE=12     ,						_SCREAMING_SNAKE_CASE=4     ,						_SCREAMING_SNAKE_CASE=1024     ,						_SCREAMING_SNAKE_CASE="gelu"     ,						_SCREAMING_SNAKE_CASE=0.1     ,						_SCREAMING_SNAKE_CASE=0.1     ,						_SCREAMING_SNAKE_CASE=512     ,						_SCREAMING_SNAKE_CASE=2     ,						_SCREAMING_SNAKE_CASE=0.0_2     ,						_SCREAMING_SNAKE_CASE=1E-12     ,						_SCREAMING_SNAKE_CASE="first"     ,						_SCREAMING_SNAKE_CASE=True     ,						_SCREAMING_SNAKE_CASE="gelu"     ,						_SCREAMING_SNAKE_CASE=0.1     ,						_SCREAMING_SNAKE_CASE=0     ,						_SCREAMING_SNAKE_CASE="absolute"     ,						_SCREAMING_SNAKE_CASE=True     ,						_SCREAMING_SNAKE_CASE=None     ,						**_SCREAMING_SNAKE_CASE     ,						)->							Optional[int]:
													super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE     ,						**_SCREAMING_SNAKE_CASE							)

													lowerCamelCase_								=vocab_size
													lowerCamelCase_								=embedding_size
													lowerCamelCase_								=hidden_size
													lowerCamelCase_								=num_hidden_layers
													lowerCamelCase_								=num_attention_heads
													lowerCamelCase_								=intermediate_size
													lowerCamelCase_								=hidden_act
													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_								=summary_type
													lowerCamelCase_								=summary_use_proj
													lowerCamelCase_								=summary_activation
													lowerCamelCase_								=summary_last_dropout
													lowerCamelCase_								=position_embedding_type
													lowerCamelCase_								=use_cache
													lowerCamelCase_								=classifier_dropout


class 			_SCREAMING_SNAKE_CASE      (  lowerCAmelCase__):







						@property
						def        _snake_case				(			self							)->							Mapping[str, Mapping[int, str]]:
													if self.task == "multiple-choice":
																				lowerCamelCase_								={0: """batch""", 1: """choice""", 2: """sequence"""}
													else:
																				lowerCamelCase_								={0: """batch""", 1: """sequence"""}
													return OrderedDict(
													    [
													        ("""input_ids""", dynamic_axis),
													        ("""attention_mask""", dynamic_axis),
													        ("""token_type_ids""", dynamic_axis),
													    ]							)
