


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							:					Union[str, Any]     						=     {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}






class     UpperCamelCase(  _a   ):

					'''simple docstring'''





					snake_case_		:				Optional[Any]										=	"""camembert"""


					def __init__(						self	:		str     ,    SCREAMING_SNAKE_CASE	:		Optional[int]=3_0_5_2_2     ,    SCREAMING_SNAKE_CASE	:		List[Any]=7_6_8     ,    SCREAMING_SNAKE_CASE	:		Tuple=1_2     ,    SCREAMING_SNAKE_CASE	:		Optional[int]=1_2     ,    SCREAMING_SNAKE_CASE	:		Any=3_0_7_2     ,    SCREAMING_SNAKE_CASE	:		Union[str, Any]="gelu"     ,    SCREAMING_SNAKE_CASE	:		Optional[int]=0.1     ,    SCREAMING_SNAKE_CASE	:		int=0.1     ,    SCREAMING_SNAKE_CASE	:		Optional[Any]=5_1_2     ,    SCREAMING_SNAKE_CASE	:		Union[str, Any]=2     ,    SCREAMING_SNAKE_CASE	:		Any=0.02     ,    SCREAMING_SNAKE_CASE	:		List[Any]=1e-1_2     ,    SCREAMING_SNAKE_CASE	:		List[str]=1     ,    SCREAMING_SNAKE_CASE	:		List[str]=0     ,    SCREAMING_SNAKE_CASE	:		int=2     ,    SCREAMING_SNAKE_CASE	:		Dict="absolute"     ,    SCREAMING_SNAKE_CASE	:		List[str]=True     ,    SCREAMING_SNAKE_CASE	:		int=None     ,    **SCREAMING_SNAKE_CASE	:		Tuple     ,    )			->	Any:




											'''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						)

											__snake_case				=		vocab_size
											__snake_case				=		hidden_size
											__snake_case				=		num_hidden_layers
											__snake_case				=		num_attention_heads
											__snake_case				=		hidden_act
											__snake_case				=		intermediate_size
											__snake_case				=		hidden_dropout_prob
											__snake_case				=		attention_probs_dropout_prob
											__snake_case				=		max_position_embeddings
											__snake_case				=		type_vocab_size
											__snake_case				=		initializer_range
											__snake_case				=		layer_norm_eps
											__snake_case				=		position_embedding_type
											__snake_case				=		use_cache
											__snake_case				=		classifier_dropout






class     UpperCamelCase(  _a   ):

					'''simple docstring'''





					@property
					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[Any]						)			->	Mapping[str, Mapping[int, str]]:




											'''simple docstring'''

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









import os
from typing import Dict, List, Tuple, TypeVar, Union


A							:					List[Any]     						=     TypeVar('T')

A							:					Dict     						=     Union[List[T], Tuple[T, ...]]
A							:					Any     						=     Union[T, List[T], Dict[str, T]]
A							:					Optional[int]     						=     Union[str, bytes, os.PathLike]





