




from collections import OrderedDict
from typing import Mapping

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


__SCREAMING_SNAKE_CASE			:      Dict      			=logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE			:      Optional[int]      			={
    """flaubert/flaubert_small_cased""": """https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json""",
    """flaubert/flaubert_base_uncased""": """https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json""",
    """flaubert/flaubert_base_cased""": """https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json""",
    """flaubert/flaubert_large_cased""": """https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json""",
}






class 	A	(						_lowerCAmelCase						):
     """simple docstring"""

     _snake_case:		Optional[int]   ="flaubert"
     _snake_case:		Optional[Any]   ={
         "hidden_size": "emb_dim",
         "num_attention_heads": "n_heads",
         "num_hidden_layers": "n_layers",
         "n_words": "vocab_size",  # For backward compatibility
     }




     def __init__(			self     :      Union[str, Any]		,     A__     :      int=False		,     A__     :      str=0.0		,     A__     :      str=3_0_1_4_5		,     A__     :      Union[str, Any]=2_0_4_8		,     A__     :      Dict=1_2		,     A__     :      Dict=1_6		,     A__     :      Dict=0.1		,     A__     :      Any=0.1		,     A__     :      Tuple=True		,     A__     :      List[Any]=False		,     A__     :      Optional[int]=False		,     A__     :      str=False		,     A__     :      Optional[int]=1		,     A__     :      int=True		,     A__     :      Dict=5_1_2		,     A__     :      List[Any]=2_0_4_8**-0.5		,     A__     :      Union[str, Any]=1E-12		,     A__     :      Optional[Any]=0.02		,     A__     :      int=0		,     A__     :      str=1		,     A__     :      List[str]=2		,     A__     :      Dict=3		,     A__     :      List[Any]=5		,     A__     :      Optional[int]=True		,     A__     :      Optional[int]="first"		,     A__     :      Tuple=True		,     A__     :      str=None		,     A__     :      Union[str, Any]=True		,     A__     :      Any=0.1		,     A__     :      Any=5		,     A__     :      Dict=5		,     A__     :      Optional[Any]=0		,     A__     :      Union[str, Any]=0		,     A__     :      str=2		,     A__     :      Union[str, Any]=0		,     **A__     :      int		,     ) ->				Any:
           lowerCamelCase__					     = pre_norm
           lowerCamelCase__					     = layerdrop
           lowerCamelCase__					     = vocab_size
           lowerCamelCase__					     = emb_dim
           lowerCamelCase__					     = n_layers
           lowerCamelCase__					     = n_heads
           lowerCamelCase__					     = dropout
           lowerCamelCase__					     = attention_dropout
           lowerCamelCase__					     = gelu_activation
           lowerCamelCase__					     = sinusoidal_embeddings
           lowerCamelCase__					     = causal
           lowerCamelCase__					     = asm
           lowerCamelCase__					     = n_langs
           lowerCamelCase__					     = use_lang_emb
           lowerCamelCase__					     = layer_norm_eps
           lowerCamelCase__					     = bos_index
           lowerCamelCase__					     = eos_index
           lowerCamelCase__					     = pad_index
           lowerCamelCase__					     = unk_index
           lowerCamelCase__					     = mask_index
           lowerCamelCase__					     = is_encoder
           lowerCamelCase__					     = max_position_embeddings
           lowerCamelCase__					     = embed_init_std
           lowerCamelCase__					     = init_std
           lowerCamelCase__					     = summary_type
           lowerCamelCase__					     = summary_use_proj
           lowerCamelCase__					     = summary_activation
           lowerCamelCase__					     = summary_proj_to_labels
           lowerCamelCase__					     = summary_first_dropout
           lowerCamelCase__					     = start_n_top
           lowerCamelCase__					     = end_n_top
           lowerCamelCase__					     = mask_token_id
           lowerCamelCase__					     = lang_id

           if "n_words" in kwargs:
                 lowerCamelCase__					     = kwargs['n_words']

           super().__init__(pad_token_id=A__		,     bos_token_id=A__		,     **A__	)






class 	A	(						_lowerCAmelCase						):
     """simple docstring"""

     @property
     def        __snake_case      (			self     :      Optional[Any]	) ->				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),
               ]	)






"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_vilt import ViltImageProcessor


a__    :   str    						= logging.get_logger(__name__)



class    lowercase_ (   __lowerCAmelCase							):

       def __init__(	self      ,    *__SCREAMING_SNAKE_CASE      ,    **__SCREAMING_SNAKE_CASE   ):






        '''simple docstring'''

        warnings.warn(
            "The class ViltFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
            " use ViltImageProcessor instead."      ,    __SCREAMING_SNAKE_CASE      ,    )
        super().__init__(*__SCREAMING_SNAKE_CASE      ,    **__SCREAMING_SNAKE_CASE   )

