




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					:       Optional[int]    					=      logging.get_logger(__name__)

__UpperCamelCase					:       Optional[int]    					=      {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__UpperCamelCase					:       List[str]    					=      {
    "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					:       Optional[int]    					=      {
    "junnyu/roformer_chinese_small": 1_536,
    "junnyu/roformer_chinese_base": 1_536,
    "junnyu/roformer_chinese_char_small": 512,
    "junnyu/roformer_chinese_char_base": 512,
    "junnyu/roformer_small_discriminator": 128,
    "junnyu/roformer_small_generator": 128,
}


__UpperCamelCase					:       Optional[int]    					=      {
    "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 		__lowerCAmelCase	(	__magic_name__ ):
							UpperCamelCase__					     =  VOCAB_FILES_NAMES
							UpperCamelCase__					     =  PRETRAINED_VOCAB_FILES_MAP
							UpperCamelCase__					     =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							UpperCamelCase__					     =  PRETRAINED_INIT_CONFIGURATION
							UpperCamelCase__					     =  RoFormerTokenizer
							def __init__(						self						:str		,      __magic_name__						:int=None		,      __magic_name__						:Union[str, Any]=None		,      __magic_name__						:str=True		,      __magic_name__						:Optional[Any]="[UNK]"		,      __magic_name__						:str="[SEP]"		,      __magic_name__						:Optional[Any]="[PAD]"		,      __magic_name__						:Tuple="[CLS]"		,      __magic_name__						:Any="[MASK]"		,      __magic_name__						:Optional[Any]=True		,      __magic_name__						:Optional[int]=None		,      **__magic_name__						:List[str]		,      ):







								'''simple docstring'''







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

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

								a										=							do_lower_case
							def __getstate__(						self						:Dict				):







								'''simple docstring'''







								a										=							self.__dict__.copy()
								a										=							BertPreTokenizer()
								return state
							def __setstate__(						self						:str		,      __magic_name__						:List[str]				):







								'''simple docstring'''







								a										=							d
								a										=							self.__dict__["""_tokenizer"""].get_vocab()
								a										=							PreTokenizer.custom(JiebaPreTokenizer(__magic_name__				)				)
							def       lowerCamelCase__							(						self						:Union[str, Any]		,      __magic_name__						:Tuple		,      __magic_name__						:Tuple=None				):







								'''simple docstring'''







								a										=							[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       lowerCamelCase__							(						self						:Any		,      __magic_name__						:List[int]		,      __magic_name__						:Optional[List[int]] = None				):







								'''simple docstring'''







								a										=							[self.sep_token_id]
								a										=							[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       lowerCamelCase__							(						self						:str		,      __magic_name__						:str		,      __magic_name__						:Optional[str] = None				):







								'''simple docstring'''







								a										=							self._tokenizer.model.save(__magic_name__		,      name=__magic_name__				)
								return tuple(__magic_name__				)





							def       lowerCamelCase__							(						self						:Union[str, Any]		,      __magic_name__						:Union[str, Any]		,      __magic_name__						:Optional[int]=None		,      __magic_name__						:Optional[Any]=None		,      __magic_name__						:int=False		,      **__magic_name__						:Optional[Any]		,      ):







								'''simple docstring'''







								a										=							BertPreTokenizer()
								return super().save_pretrained(__magic_name__		,      __magic_name__		,      __magic_name__		,      __magic_name__		,      **__magic_name__				)







def 		__A		(	__lowerCamelCase							,			__lowerCamelCase    )      ->       str:
	if not isinstance(__lowerCamelCase							,			__lowerCamelCase    ):
		raise ValueError("""iterations must be defined as integers"""    )
	if not isinstance(__lowerCamelCase							,			__lowerCamelCase    ) or not number >= 1:
		raise ValueError(
		    """starting number must be
                         and integer and be more than 0"""    )
	if not iterations >= 1:
		raise ValueError("""Iterations must be done more than 0 times to play FizzBuzz"""    )

	a										=							""""""
	while number <= iterations:
		if number % 3 == 0:
			out += "Fizz"
		if number % 5 == 0:
			out += "Buzz"
		if 0 not in (number % 3, number % 5):
			out += str(__lowerCamelCase    )

		# print(out)
		number += 1
		out += " "
	return out


if __name__ == "__main__":
		import doctest

		doctest.testmod()

