






from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


lowerCAmelCase_			      = {
    'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
    'susnato/ernie-m-large_pytorch': 'https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json',
}
class      UpperCamelCase (				__lowerCamelCase ):







		"""simple docstring"""



		snake_case    =   "ernie_m"
		snake_case    =   {"dropout": "classifier_dropout", "num_classes": "num_labels"}
		def __init__(  self		:       Any						,_SCREAMING_SNAKE_CASE		:       Optional[Any] = 2_5_0_0_0_2						,_SCREAMING_SNAKE_CASE		:       Optional[int] = 7_6_8						,_SCREAMING_SNAKE_CASE		:       Dict = 1_2						,_SCREAMING_SNAKE_CASE		:       Tuple = 1_2						,_SCREAMING_SNAKE_CASE		:       Union[str, Any] = 3_0_7_2						,_SCREAMING_SNAKE_CASE		:       Any = "gelu"						,_SCREAMING_SNAKE_CASE		:       str = 0.1						,_SCREAMING_SNAKE_CASE		:       Tuple = 0.1						,_SCREAMING_SNAKE_CASE		:       Tuple = 5_1_4						,_SCREAMING_SNAKE_CASE		:       Optional[int] = 0.02						,_SCREAMING_SNAKE_CASE		:       int = 1						,_SCREAMING_SNAKE_CASE		:       int = 1E-05						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=None						,_SCREAMING_SNAKE_CASE		:       str=False						,_SCREAMING_SNAKE_CASE		:       List[str]=0.0						,**_SCREAMING_SNAKE_CASE		:       Dict						,)    ->   str:


						'''simple docstring'''
						super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_						,**SCREAMING_SNAKE_CASE_		)
						A	 =      vocab_size
						A	 =      hidden_size
						A	 =      num_hidden_layers
						A	 =      num_attention_heads
						A	 =      intermediate_size
						A	 =      hidden_act
						A	 =      hidden_dropout_prob
						A	 =      attention_probs_dropout_prob
						A	 =      max_position_embeddings
						A	 =      initializer_range
						A	 =      layer_norm_eps
						A	 =      classifier_dropout
						A	 =      is_decoder
						A	 =      act_dropout













from ...configuration_utils import PretrainedConfig
class      UpperCamelCase (				snake_case__ ):







		"""simple docstring"""



		snake_case    =   "bert-generation"
		def __init__(  self		:       Tuple						,_SCREAMING_SNAKE_CASE		:       Tuple=5_0_3_5_8						,_SCREAMING_SNAKE_CASE		:       str=1_0_2_4						,_SCREAMING_SNAKE_CASE		:       List[str]=2_4						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=1_6						,_SCREAMING_SNAKE_CASE		:       Dict=4_0_9_6						,_SCREAMING_SNAKE_CASE		:       str="gelu"						,_SCREAMING_SNAKE_CASE		:       str=0.1						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=0.1						,_SCREAMING_SNAKE_CASE		:       Tuple=5_1_2						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=0.02						,_SCREAMING_SNAKE_CASE		:       List[str]=1E-12						,_SCREAMING_SNAKE_CASE		:       Tuple=0						,_SCREAMING_SNAKE_CASE		:       Union[str, Any]=2						,_SCREAMING_SNAKE_CASE		:       Optional[int]=1						,_SCREAMING_SNAKE_CASE		:       str="absolute"						,_SCREAMING_SNAKE_CASE		:       Optional[int]=True						,**_SCREAMING_SNAKE_CASE		:       Optional[int]						,)    ->   Dict:


						'''simple docstring'''
						super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE						,bos_token_id=_SCREAMING_SNAKE_CASE						,eos_token_id=_SCREAMING_SNAKE_CASE						,**_SCREAMING_SNAKE_CASE		)

						A	 =      vocab_size
						A	 =      hidden_size
						A	 =      num_hidden_layers
						A	 =      num_attention_heads
						A	 =      hidden_act
						A	 =      intermediate_size
						A	 =      hidden_dropout_prob
						A	 =      attention_probs_dropout_prob
						A	 =      max_position_embeddings
						A	 =      initializer_range
						A	 =      layer_norm_eps
						A	 =      position_embedding_type
						A	 =      use_cache





