


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 :					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  UpperCamelCase__ ( __lowerCamelCase			):
      a__   :     Tuple								=						'flaubert'
      a__   :     List[str]								=						{
          'hidden_size': 'emb_dim',
          'num_attention_heads': 'n_heads',
          'num_hidden_layers': 'n_layers',
          'n_words': 'vocab_size',  # For backward compatibility
      }






      def __init__(     self					:   Optional[int],		__lowerCamelCase					:   List[str]=False,		__lowerCamelCase					:   Dict=0.0,		__lowerCamelCase					:   Optional[Any]=3_01_45,		__lowerCamelCase					:   Dict=20_48,		__lowerCamelCase					:   int=12,		__lowerCamelCase					:   Any=16,		__lowerCamelCase					:   Optional[Any]=0.1,		__lowerCamelCase					:   List[str]=0.1,		__lowerCamelCase					:   str=True,		__lowerCamelCase					:   Any=False,		__lowerCamelCase					:   Dict=False,		__lowerCamelCase					:   int=False,		__lowerCamelCase					:   Any=1,		__lowerCamelCase					:   str=True,		__lowerCamelCase					:   Union[str, Any]=5_12,		__lowerCamelCase					:   Optional[int]=20_48**-0.5,		__lowerCamelCase					:   Tuple=1e-12,		__lowerCamelCase					:   Dict=0.02,		__lowerCamelCase					:   Tuple=0,		__lowerCamelCase					:   Union[str, Any]=1,		__lowerCamelCase					:   int=2,		__lowerCamelCase					:   List[Any]=3,		__lowerCamelCase					:   int=5,		__lowerCamelCase					:   Optional[int]=True,		__lowerCamelCase					:   str="first",		__lowerCamelCase					:   List[str]=True,		__lowerCamelCase					:   List[str]=None,		__lowerCamelCase					:   List[str]=True,		__lowerCamelCase					:   List[Any]=0.1,		__lowerCamelCase					:   Union[str, Any]=5,		__lowerCamelCase					:   Union[str, Any]=5,		__lowerCamelCase					:   List[Any]=0,		__lowerCamelCase					:   Tuple=0,		__lowerCamelCase					:   Optional[Any]=2,		__lowerCamelCase					:   str=0,		**__lowerCamelCase					:   Any,		)  -> Any:
           UpperCamelCase__							:  int								=     pre_norm
           UpperCamelCase__							:  Union[str, Any]								=     layerdrop
           UpperCamelCase__							:  int								=     vocab_size
           UpperCamelCase__							:  str								=     emb_dim
           UpperCamelCase__							:  Optional[int]								=     n_layers
           UpperCamelCase__							:  Union[str, Any]								=     n_heads
           UpperCamelCase__							:  str								=     dropout
           UpperCamelCase__							:  int								=     attention_dropout
           UpperCamelCase__							:  Optional[Any]								=     gelu_activation
           UpperCamelCase__							:  Optional[Any]								=     sinusoidal_embeddings
           UpperCamelCase__							:  Optional[int]								=     causal
           UpperCamelCase__							:  Tuple								=     asm
           UpperCamelCase__							:  Tuple								=     n_langs
           UpperCamelCase__							:  List[str]								=     use_lang_emb
           UpperCamelCase__							:  Optional[Any]								=     layer_norm_eps
           UpperCamelCase__							:  Optional[int]								=     bos_index
           UpperCamelCase__							:  str								=     eos_index
           UpperCamelCase__							:  List[Any]								=     pad_index
           UpperCamelCase__							:  Dict								=     unk_index
           UpperCamelCase__							:  Dict								=     mask_index
           UpperCamelCase__							:  str								=     is_encoder
           UpperCamelCase__							:  Any								=     max_position_embeddings
           UpperCamelCase__							:  Union[str, Any]								=     embed_init_std
           UpperCamelCase__							:  Optional[Any]								=     init_std
           UpperCamelCase__							:  Optional[int]								=     summary_type
           UpperCamelCase__							:  int								=     summary_use_proj
           UpperCamelCase__							:  str								=     summary_activation
           UpperCamelCase__							:  Dict								=     summary_proj_to_labels
           UpperCamelCase__							:  List[Any]								=     summary_first_dropout
           UpperCamelCase__							:  Optional[int]								=     start_n_top
           UpperCamelCase__							:  Optional[Any]								=     end_n_top
           UpperCamelCase__							:  Union[str, Any]								=     mask_token_id
           UpperCamelCase__							:  List[Any]								=     lang_id

           if "n_words" in kwargs:
                UpperCamelCase__							:  List[Any]								=     kwargs['''n_words''']

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

class  UpperCamelCase__ ( __lowerCamelCase			):






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








import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


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

class  UpperCamelCase__ ( __lowerCamelCase			):






      def __init__(     self					:   List[str],		*__lowerCamelCase					:   Optional[int],		**__lowerCamelCase					:   Dict   )  -> None:
           warnings.warn(
               '''The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
               ''' Please use MobileNetV1ImageProcessor instead.''',		__lowerCamelCase,		)
           super().__init__(*__lowerCamelCase,		**__lowerCamelCase   )




