

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

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


lowerCamelCase :      Union[str, Any]					 =     logging.get_logger(__name__)

lowerCamelCase :      Optional[int]					 =     {
    "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 							A__    (       A__  ):
  A__		 =				'camembert'





  def __init__(		self      :	Any							,					_a      :	List[str]=3_0522							,					_a      :	Union[str, Any]=768							,					_a      :	Optional[Any]=12							,					_a      :	Optional[int]=12							,					_a      :	Dict=3072							,					_a      :	Dict="gelu"							,					_a      :	Any=0.1							,					_a      :	str=0.1							,					_a      :	Optional[int]=512							,					_a      :	Optional[Any]=2							,					_a      :	Optional[int]=0.02							,					_a      :	Optional[int]=1e-12							,					_a      :	List[str]=1							,					_a      :	List[Any]=0							,					_a      :	Dict=2							,					_a      :	List[Any]="absolute"							,					_a      :	Optional[Any]=True							,					_a      :	Tuple=None							,					**_a      :	Optional[int]							,					)	->    Union[str, Any]:





       '''simple docstring'''






       super().__init__(pad_token_id=_a							,					bos_token_id=_a							,					eos_token_id=_a							,					**_a )

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







class 							A__    (       A__  ):





  @property
  def 						A  (		self      :	List[str] )	->    Mapping[str, Mapping[int, str]]:





       '''simple docstring'''






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



'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowerCamelCase :      List[str]					 =     logging.get_logger(__name__)

lowerCamelCase :      List[Any]					 =     {
    "facebook/convnextv2-tiny-1k-224": "https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json",
}







class 							A__    (       A__     ,   A__  ):
  A__		 =				'convnextv2'





  def __init__(		self      :	Tuple							,					_a      :	Optional[int]=3							,					_a      :	Any=4							,					_a      :	int=4							,					_a      :	Union[str, Any]=None							,					_a      :	List[str]=None							,					_a      :	Optional[Any]="gelu"							,					_a      :	Any=0.02							,					_a      :	Any=1e-12							,					_a      :	Tuple=0.0							,					_a      :	int=224							,					_a      :	Any=None							,					_a      :	Optional[int]=None							,					**_a      :	List[str]							,					)	->    Optional[Any]:





       '''simple docstring'''






       super().__init__(**_a )

       _SCREAMING_SNAKE_CASE							    =num_channels
       _SCREAMING_SNAKE_CASE							    =patch_size
       _SCREAMING_SNAKE_CASE							    =num_stages
       _SCREAMING_SNAKE_CASE							    =[96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
       _SCREAMING_SNAKE_CASE							    =[3, 3, 9, 3] if depths is None else depths
       _SCREAMING_SNAKE_CASE							    =hidden_act
       _SCREAMING_SNAKE_CASE							    =initializer_range
       _SCREAMING_SNAKE_CASE							    =layer_norm_eps
       _SCREAMING_SNAKE_CASE							    =drop_path_rate
       _SCREAMING_SNAKE_CASE							    =image_size
       _SCREAMING_SNAKE_CASE							    =['stem'] + [f"stage{idx}" for idx in range(1							,					len(self.depths ) + 1 )]
       _SCREAMING_SNAKE_CASE    ,						_SCREAMING_SNAKE_CASE							    =get_aligned_output_features_output_indices(
           out_features=_a							,					out_indices=_a							,					stage_names=self.stage_names )
