




'''simple docstring'''





import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


_SCREAMING_SNAKE_CASE							:       Tuple						=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:       List[Any]						=			{"vocab_file": "sentencepiece.bpe.model"}

_SCREAMING_SNAKE_CASE							:       Tuple						=			{
    "vocab_file": {
        "moussaKam/mbarthez": "https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez": "https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez-orangesum-title": (
            "https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"
        ),
    },
}

_SCREAMING_SNAKE_CASE							:       List[Any]						=			{
    "moussaKam/mbarthez": 1024,
    "moussaKam/barthez": 1024,
    "moussaKam/barthez-orangesum-title": 1024,
}

_SCREAMING_SNAKE_CASE							:       Any						=			"▁"




class 			_snake_case		(     lowercase_							):
   lowerCAmelCase_					:				List[Any]							=   VOCAB_FILES_NAMES
   lowerCAmelCase_					:				Optional[Any]							=   PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase_					:				int							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCAmelCase_					:				Tuple							=   ["input_ids", "attention_mask"]




   def __init__( self    ,							a__    ,							a__="<s>"    ,							a__="</s>"    ,							a__="</s>"    ,							a__="<s>"    ,							a__="<unk>"    ,							a__="<pad>"    ,							a__="<mask>"    ,							a__ = None    ,							**a__    ,							)    ->    None:

          '''simple docstring'''




          snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else mask_token

          snake_case_      =				{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              bos_token=a__    ,							eos_token=a__    ,							unk_token=a__    ,							sep_token=a__    ,							cls_token=a__    ,							pad_token=a__    ,							mask_token=a__    ,							sp_model_kwargs=self.sp_model_kwargs    ,							**a__    ,							)

          snake_case_      =				vocab_file
          snake_case_      =				spm.SentencePieceProcessor(**self.sp_model_kwargs							)
          self.sp_model.Load(str(a__							)							)

          snake_case_      =				{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

          snake_case_      =				len(self.sp_model							) - 1
          snake_case_      =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

          '''simple docstring'''




          if token_ids_a is None:
                 return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          snake_case_      =				[self.cls_token_id]
          snake_case_      =				[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None    ,							a__ = False							)    ->    List[int]:

          '''simple docstring'''




          if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=a__    ,							token_ids_a=a__    ,							already_has_special_tokens=a__							)

          if token_ids_a is None:
                 return [1] + ([0] * len(a__							)) + [1]
          return [1] + ([0] * len(a__							)) + [1, 1] + ([0] * len(a__							)) + [1]




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

          '''simple docstring'''




          snake_case_      =				[self.sep_token_id]
          snake_case_      =				[self.cls_token_id]

          if token_ids_a is None:
                 return len(cls + token_ids_a + sep							) * [0]
          return len(cls + token_ids_a + sep + sep + token_ids_a + sep							) * [0]




   @property
   def        lowerCAmelCase__    ( self							)    ->    List[Any]:

          '''simple docstring'''




          return len(self.sp_model							)




   def        lowerCAmelCase__    ( self							)    ->    int:

          '''simple docstring'''




          snake_case_      =				{self.convert_ids_to_tokens(a__							): i for i in range(self.vocab_size							)}
          vocab.update(self.added_tokens_encoder							)
          return vocab




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    List[str]:

          '''simple docstring'''




          return self.sp_model.encode(a__    ,							out_type=a__							)




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    int:

          '''simple docstring'''




          if token in self.fairseq_tokens_to_ids:
                 return self.fairseq_tokens_to_ids[token]
          snake_case_      =				self.sp_model.PieceToId(a__							)

          return spm_id if spm_id else self.unk_token_id




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    Tuple:

          '''simple docstring'''




          if index in self.fairseq_ids_to_tokens:
                 return self.fairseq_ids_to_tokens[index]
          return self.sp_model.IdToPiece(a__							)




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    Optional[Any]:

          '''simple docstring'''




          snake_case_      =				[]
          snake_case_      =				""
          snake_case_      =				False
          for token in tokens:
                 # make sure that special tokens are not decoded using sentencepiece model
                 if token in self.all_special_tokens:
                        if not prev_is_special:
                               out_string += " "
                        out_string += self.sp_model.decode(a__							) + token
                        snake_case_      =				True
                        snake_case_      =				[]
                 else:
                        current_sub_tokens.append(a__							)
                        snake_case_      =				False
          out_string += self.sp_model.decode(a__							)
          return out_string.strip()




   def __getstate__( self							)    ->    Dict:

          '''simple docstring'''




          snake_case_      =				self.__dict__.copy()
          snake_case_      =				None
          return state




   def __setstate__( self    ,							a__							)    ->    str:

          '''simple docstring'''




          snake_case_      =				d

          # for backward compatibility
          if not hasattr(self    ,							"sp_model_kwargs"							):
                 snake_case_      =				{}

          snake_case_      =				spm.SentencePieceProcessor(**self.sp_model_kwargs							)
          self.sp_model.Load(self.vocab_file							)




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    Tuple[str]:

          '''simple docstring'''




          if not os.path.isdir(a__							):
                 logger.error(F'Vocabulary path ({save_directory}) should be a directory'							)
                 return
          snake_case_      =				os.path.join(
              a__    ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

          if os.path.abspath(self.vocab_file							) != os.path.abspath(a__							) and os.path.isfile(self.vocab_file							):
                 copyfile(self.vocab_file    ,							a__							)
          elif not os.path.isfile(self.vocab_file							):
                 with open(a__    ,							"wb"							) as fi:
                        snake_case_      =				self.sp_model.serialized_model_proto()
                        fi.write(a__							)

          return (out_vocab_file,)










'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE							:       Any						=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:       int						=			{
    "alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}




class 			_snake_case		(     lowercase_							):
			lowerCAmelCase_					:				Union[str, Any]							=   "mgp-str"




			def __init__( self    ,							a__=[32, 128]    ,							a__=4    ,							a__=3    ,							a__=27    ,							a__=38    ,							a__=50_257    ,							a__=30_522    ,							a__=768    ,							a__=12    ,							a__=12    ,							a__=4.0    ,							a__=True    ,							a__=False    ,							a__=1e-5    ,							a__=0.0    ,							a__=0.0    ,							a__=0.0    ,							a__=False    ,							a__=0.0_2    ,							**a__    ,							)    ->    Union[str, Any]:

										'''simple docstring'''




										super().__init__(**a__							)

										snake_case_      =				image_size
										snake_case_      =				patch_size
										snake_case_      =				num_channels
										snake_case_      =				max_token_length
										snake_case_      =				num_character_labels
										snake_case_      =				num_bpe_labels
										snake_case_      =				num_wordpiece_labels
										snake_case_      =				hidden_size
										snake_case_      =				num_hidden_layers
										snake_case_      =				num_attention_heads
										snake_case_      =				mlp_ratio
										snake_case_      =				distilled
										snake_case_      =				layer_norm_eps
										snake_case_      =				drop_rate
										snake_case_      =				qkv_bias
										snake_case_      =				attn_drop_rate
										snake_case_      =				drop_path_rate
										snake_case_      =				output_aa_attentions
										snake_case_      =				initializer_range




