





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


UpperCamelCase__   : str					  = logging.get_logger(__name__)

UpperCamelCase__   : str					  = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

UpperCamelCase__   : Tuple					  = {
    """vocab_file""": {
        """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_char_small""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_chinese_char_base""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_discriminator""": (
            """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_generator""": (
            """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt"""
        ),
    }
}

UpperCamelCase__   : Union[str, Any]					  = {
    """junnyu/roformer_chinese_small""": 15_36,
    """junnyu/roformer_chinese_base""": 15_36,
    """junnyu/roformer_chinese_char_small""": 5_12,
    """junnyu/roformer_chinese_char_base""": 5_12,
    """junnyu/roformer_small_discriminator""": 1_28,
    """junnyu/roformer_small_generator""": 1_28,
}


UpperCamelCase__   : Union[str, Any]					  = {
    """junnyu/roformer_chinese_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_base""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_base""": {"""do_lower_case""": True},
    """junnyu/roformer_small_discriminator""": {"""do_lower_case""": True},
    """junnyu/roformer_small_generator""": {"""do_lower_case""": True},
}







class   _UpperCamelCase  (       A_  ):







					'''simple docstring'''

					lowerCamelCase     :     int			    =       VOCAB_FILES_NAMES
					lowerCamelCase     :     Union[str, Any]			    =       PRETRAINED_VOCAB_FILES_MAP
					lowerCamelCase     :     int			    =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCamelCase     :     Optional[Any]			    =       PRETRAINED_INIT_CONFIGURATION
					lowerCamelCase     :     Tuple			    =       RoFormerTokenizer





					def __init__(						self    :  str ,					__lowercase    :  Tuple=None ,					__lowercase    :  List[str]=None ,					__lowercase    :  int=True ,					__lowercase    :  List[Any]="[UNK]" ,					__lowercase    :  Any="[SEP]" ,					__lowercase    :  List[str]="[PAD]" ,					__lowercase    :  int="[CLS]" ,					__lowercase    :  Optional[int]="[MASK]" ,					__lowercase    :  List[str]=True ,					__lowercase    :  Optional[Any]=None ,					**__lowercase    :  Optional[int] ,					):






						'''simple docstring'''







						super().__init__(
						    __lowercase ,					tokenizer_file=__lowercase ,					do_lower_case=__lowercase ,					unk_token=__lowercase ,					sep_token=__lowercase ,					pad_token=__lowercase ,					cls_token=__lowercase ,					mask_token=__lowercase ,					tokenize_chinese_chars=__lowercase ,					strip_accents=__lowercase ,					**__lowercase ,					)

						UpperCAmelCase_								=     json.loads(self.backend_tokenizer.normalizer.__getstate__()		)
						if (
						    pre_tok_state.get("""lowercase""" ,					__lowercase		) != do_lower_case
						    or pre_tok_state.get("""strip_accents""" ,					__lowercase		) != strip_accents
						):
							UpperCAmelCase_								=     getattr(__lowercase ,					pre_tok_state.pop("""type"""		)		)
							UpperCAmelCase_								=     do_lower_case
							UpperCAmelCase_								=     strip_accents
							UpperCAmelCase_								=     pre_tok_class(**__lowercase		)

						UpperCAmelCase_								=     do_lower_case





					def __getstate__(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.__dict__.copy()
						UpperCAmelCase_								=     BertPreTokenizer()
						return state





					def __setstate__(						self    :  int ,					__lowercase    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     d
						UpperCAmelCase_								=     self.__dict__["""_tokenizer"""].get_vocab()
						UpperCAmelCase_								=     PreTokenizer.custom(JiebaPreTokenizer(__lowercase		)		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple ,					__lowercase    :  Union[str, Any] ,					__lowercase    :  Any=None		):






						'''simple docstring'''







						UpperCAmelCase_								=     [self.cls_token_id] + token_ids_a + [self.sep_token_id]

						if token_ids_a:
							output += token_ids_a + [self.sep_token_id]

						return output





					def        SCREAMING_SNAKE_CASE							(						self    :  int ,					__lowercase    :  List[int] ,					__lowercase    :  Optional[List[int]] = None		):






						'''simple docstring'''







						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		) * [0] + len(token_ids_a + sep		) * [1]





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any] ,					__lowercase    :  str ,					__lowercase    :  Optional[str] = None		):






						'''simple docstring'''







						UpperCAmelCase_								=     self._tokenizer.model.save(__lowercase ,					name=__lowercase		)
						return tuple(__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str ,					__lowercase    :  List[Any] ,					__lowercase    :  Optional[Any]=None ,					__lowercase    :  Dict=None ,					__lowercase    :  Tuple=False ,					**__lowercase    :  Any ,					):






						'''simple docstring'''







						UpperCAmelCase_								=     BertPreTokenizer()
						return super().save_pretrained(__lowercase ,					__lowercase ,					__lowercase ,					__lowercase ,					**__lowercase		)









import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer




def    A_(			A				,      A				,      **A   ):
	UpperCAmelCase_								=     AutoConfig.from_pretrained(A				,      **A   )
	UpperCAmelCase_								=     AutoModelForSeqaSeqLM.from_config(A   )
	model.save_pretrained(A   )
	AutoTokenizer.from_pretrained(A   ).save_pretrained(A   )
	return model


if __name__ == "__main__":
				fire.Fire(save_randomly_initialized_version)


