

from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE		:List[Any]						=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:str						=     {
    """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json""",
    """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json""",
    """junnyu/roformer_chinese_char_small""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json"""
    ),
    """junnyu/roformer_chinese_char_base""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_discriminator""": (
        """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_generator""": (
        """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json"""
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:List[str]										=      """roformer"""






     def __init__(				self		,						_lowercase=50_000		,						_lowercase=None		,						_lowercase=768		,						_lowercase=12		,						_lowercase=12		,						_lowercase=3_072		,						_lowercase="gelu"		,						_lowercase=0.1		,						_lowercase=0.1		,						_lowercase=1_536		,						_lowercase=2		,						_lowercase=0.02		,						_lowercase=1e-1_2		,						_lowercase=0		,						_lowercase=False		,						_lowercase=True		,						**_lowercase		,						)->     Any:
         super().__init__(pad_token_id=_lowercase		,						**_lowercase	)

         UpperCamelCase_			  =						vocab_size
         UpperCamelCase_			  =						hidden_size if embedding_size is None else embedding_size
         UpperCamelCase_			  =						hidden_size
         UpperCamelCase_			  =						num_hidden_layers
         UpperCamelCase_			  =						num_attention_heads
         UpperCamelCase_			  =						hidden_act
         UpperCamelCase_			  =						intermediate_size
         UpperCamelCase_			  =						hidden_dropout_prob
         UpperCamelCase_			  =						attention_probs_dropout_prob
         UpperCamelCase_			  =						max_position_embeddings
         UpperCamelCase_			  =						type_vocab_size
         UpperCamelCase_			  =						initializer_range
         UpperCamelCase_			  =						layer_norm_eps
         UpperCamelCase_			  =						rotary_value
         UpperCamelCase_			  =						use_cache






class 						__magic_name__					(							snake_case				):






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



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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_barthez import BarthezTokenizer
else:
 SCREAMING_SNAKE_CASE		:Optional[Any]						=     None

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

SCREAMING_SNAKE_CASE		:Optional[Any]						=     {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

SCREAMING_SNAKE_CASE		:int						=     {
    """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"""
        ),
    },
    """tokenizer_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json"""
        ),
    },
}

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

SCREAMING_SNAKE_CASE		:Optional[Any]						=     """▁"""






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:Dict										=      VOCAB_FILES_NAMES
     UpperCamelCase_	:Optional[int]										=      PRETRAINED_VOCAB_FILES_MAP
     UpperCamelCase_	:Any										=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCamelCase_	:Any										=      ["""input_ids""", """attention_mask"""]
     UpperCamelCase_	:List[Any]										=      BarthezTokenizer






     def __init__(				self		,						_lowercase=None		,						_lowercase=None		,						_lowercase="<s>"		,						_lowercase="</s>"		,						_lowercase="</s>"		,						_lowercase="<s>"		,						_lowercase="<unk>"		,						_lowercase="<pad>"		,						_lowercase="<mask>"		,						**_lowercase		,						)->     Optional[int]:
         # Mask token behave like a normal word, i.e. include the space before it
         UpperCamelCase_			  =						AddedToken(_lowercase		,						lstrip=_lowercase		,						rstrip=_lowercase	) if isinstance(_lowercase		,						_lowercase	) else mask_token

         super().__init__(
             _lowercase		,						tokenizer_file=_lowercase		,						bos_token=_lowercase		,						eos_token=_lowercase		,						unk_token=_lowercase		,						sep_token=_lowercase		,						cls_token=_lowercase		,						pad_token=_lowercase		,						mask_token=_lowercase		,						**_lowercase		,						)

         UpperCamelCase_			  =						vocab_file
         UpperCamelCase_			  =						False if not self.vocab_file else True






     def 	UpperCAmelCase_				(				self		,						_lowercase		,						_lowercase = None	)->     List[int]:

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






     def 	UpperCAmelCase_				(				self		,						_lowercase		,						_lowercase = None	)->     List[int]:
         UpperCamelCase_			  =						[self.sep_token_id]
         UpperCamelCase_			  =						[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]






     def 	UpperCAmelCase_				(				self		,						_lowercase		,						_lowercase = None	)->     Tuple[str]:
         if not self.can_save_slow_tokenizer:
             raise ValueError(
                 "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                 "tokenizer."	)

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

         if os.path.abspath(self.vocab_file	) != os.path.abspath(_lowercase	):
             copyfile(self.vocab_file		,						_lowercase	)

         return (out_vocab_file,)
