
from collections import OrderedDict
from typing import Mapping

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


_lowerCamelCase           =logging.get_logger(__name__)

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

       if "n_words" in kwargs:
        lowerCamelCase	:			str           =   kwargs["""n_words"""]

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





class 							A__	(			__SCREAMING_SNAKE_CASE):
      @property
      def 		UpperCamelCase__							(   self   ):
       if self.task == "multiple-choice":
        lowerCamelCase	:			Optional[Any]           =   {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
        lowerCamelCase	:			List[str]           =   {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]   )






from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_lowerCamelCase           =logging.get_logger(__name__)





class 							A__	(			__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase       :					Tuple					 =    ["""input_ids""", """attention_mask"""]
      def __init__(   self					,						__magic_name__="[PAD]"					,						__magic_name__="[BOS]"					,						__magic_name__="[EOS]"					,						__magic_name__="[MASK]"					,						__magic_name__="[CLS]"					,						__magic_name__="[SEP]"					,						__magic_name__=2_0_4_8					,						**__magic_name__					,						):
       lowerCamelCase	:			List[str]           =   AddedToken(__magic_name__					,						lstrip=__magic_name__					,						rstrip=__magic_name__   ) if isinstance(__magic_name__					,						__magic_name__   ) else pad_token
       lowerCamelCase	:			Dict           =   AddedToken(__magic_name__					,						lstrip=__magic_name__					,						rstrip=__magic_name__   ) if isinstance(__magic_name__					,						__magic_name__   ) else bos_token
       lowerCamelCase	:			Any           =   AddedToken(__magic_name__					,						lstrip=__magic_name__					,						rstrip=__magic_name__   ) if isinstance(__magic_name__					,						__magic_name__   ) else eos_token
       lowerCamelCase	:			Any           =   AddedToken(__magic_name__					,						lstrip=__magic_name__					,						rstrip=__magic_name__   ) if isinstance(__magic_name__					,						__magic_name__   ) else mask_token
       lowerCamelCase	:			Any           =   AddedToken(__magic_name__					,						lstrip=__magic_name__					,						rstrip=__magic_name__   ) if isinstance(__magic_name__					,						__magic_name__   ) else cls_token
       lowerCamelCase	:			Optional[Any]           =   AddedToken(__magic_name__					,						lstrip=__magic_name__					,						rstrip=__magic_name__   ) if isinstance(__magic_name__					,						__magic_name__   ) else sep_token

       super().__init__(
           pad_token=__magic_name__					,						bos_token=__magic_name__					,						eos_token=__magic_name__					,						mask_token=__magic_name__					,						cls_token=__magic_name__					,						sep_token=__magic_name__					,						model_max_length=__magic_name__					,						**__magic_name__					,						)

       lowerCamelCase	:			List[Any]           =   2**8  # utf is 8 bits

       # define special tokens dict
       lowerCamelCase	:			Dict[str, int]           =   {
           self.pad_token: 0,
           self.bos_token: 1,
           self.eos_token: 2,
           self.mask_token: 3,
           self.cls_token: 4,
           self.sep_token: 5,
       }
       lowerCamelCase	:			Optional[int]           =   len(self.special_tokens_encoder   )
       lowerCamelCase	:			Dict[int, str]           =   {v: k for k, v in self.special_tokens_encoder.items()}
      def 		UpperCamelCase__							(   self   ):
       lowerCamelCase	:			List[str]           =   self.special_tokens_encoder.copy()
       vocab.update(self.added_tokens_encoder   )
       for i in range(self._utf_vocab_size   ):
        lowerCamelCase	:			List[Any]           =   chr(__magic_name__   )
        lowerCamelCase	:			Union[str, Any]           =   i + len(self.special_tokens_encoder   )
       return vocab
      @property
      def 		UpperCamelCase__							(   self   ):
       return self._utf_vocab_size + self._num_special_tokens
      def 		UpperCamelCase__							(   self					,						__magic_name__					,						__magic_name__ = None					,						__magic_name__ = False   ):
       if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=__magic_name__					,						token_ids_a=__magic_name__					,						already_has_special_tokens=__magic_name__   )

       # normal case: some special tokens
       if token_ids_a is None:
        return [1] + [0] * len(__magic_name__   ) + [1]
       return [1] + ([0] * len(__magic_name__   )) + [1] + ([0] * len(__magic_name__   )) + [1]
      def 		UpperCamelCase__							(   self					,						__magic_name__					,						__magic_name__ = None   ):
       if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       else:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]
      def 		UpperCamelCase__							(   self					,						__magic_name__   ):
       lowerCamelCase	:			Optional[int]           =   [chr(__magic_name__   ) for i in text.encode("""utf-8"""   )]
       return tokens
      def 		UpperCamelCase__							(   self					,						__magic_name__   ):
       if token in self.special_tokens_encoder:
        lowerCamelCase	:			List[str]           =   self.special_tokens_encoder[token]
       elif token in self.added_tokens_encoder:
        lowerCamelCase	:			List[Any]           =   self.added_tokens_encoder[token]
       elif len(__magic_name__   ) != 1:
        lowerCamelCase	:			Union[str, Any]           =   self.unk_token_id
       else:
        lowerCamelCase	:			int           =   ord(__magic_name__   ) + self._num_special_tokens
       return token_id
      def 		UpperCamelCase__							(   self					,						__magic_name__   ):
       if index in self.special_tokens_decoder:
        lowerCamelCase	:			Union[str, Any]           =   self.special_tokens_decoder[index]
       elif index in self.added_tokens_decoder:
        lowerCamelCase	:			List[str]           =   self.added_tokens_decoder[index]
       else:
        lowerCamelCase	:			Optional[int]           =   chr(index - self._num_special_tokens   )
       return token
      def 		UpperCamelCase__							(   self					,						__magic_name__   ):
       lowerCamelCase	:			List[Any]           =   b""""""
       for token in tokens:
        if token in self.special_tokens_decoder:
         lowerCamelCase	:			List[str]           =   self.special_tokens_decoder[token].encode("""utf-8"""   )
        elif token in self.added_tokens_decoder:
         lowerCamelCase	:			Optional[int]           =   self.special_tokens_decoder[token].encode("""utf-8"""   )
        elif token in self.special_tokens_encoder:
         lowerCamelCase	:			Tuple           =   token.encode("""utf-8"""   )
        elif token in self.added_tokens_encoder:
         lowerCamelCase	:			Union[str, Any]           =   token.encode("""utf-8"""   )
        else:
         lowerCamelCase	:			Dict           =   bytes([ord(__magic_name__   )]   )
        bstring += tok_string
       lowerCamelCase	:			Any           =   bstring.decode("""utf-8"""					,						errors="""replace"""   )
       return string






      def 		UpperCamelCase__							(   self					,						__magic_name__					,						__magic_name__ = None   ):
       return ()




