
'''simple docstring'''
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


lowercase__						       =      logging.get_logger(__name__)

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

lowercase__						       =      {
    """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"""
        ),
    }
}

lowercase__						       =      {
    """junnyu/roformer_chinese_small""": 1_5_3_6,
    """junnyu/roformer_chinese_base""": 1_5_3_6,
    """junnyu/roformer_chinese_char_small""": 5_1_2,
    """junnyu/roformer_chinese_char_base""": 5_1_2,
    """junnyu/roformer_small_discriminator""": 1_2_8,
    """junnyu/roformer_small_generator""": 1_2_8,
}


lowercase__						       =      {
    """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 	snake_case__       (      __SCREAMING_SNAKE_CASE					):







		"""simple docstring"""

		lowerCamelCase     							=						VOCAB_FILES_NAMES
		lowerCamelCase     							=						PRETRAINED_VOCAB_FILES_MAP
		lowerCamelCase     							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCamelCase     							=						PRETRAINED_INIT_CONFIGURATION
		lowerCamelCase     							=						RoFormerTokenizer



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

				snake_case  :       Dict     			=						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
				):
						snake_case  :       Tuple     			=						getattr(_lowercase  ,	pre_tok_state.pop('''type'''      )      )
						snake_case  :       Optional[Any]     			=						do_lower_case
						snake_case  :       Tuple     			=						strip_accents
						snake_case  :       Dict     			=						pre_tok_class(**_lowercase      )

				snake_case  :       Any     			=						do_lower_case



		def __getstate__(      self				:			List[Any]      )						->			Dict:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						self.__dict__.copy()
				snake_case  :       Optional[int]     			=						BertPreTokenizer()
				return state



		def __setstate__(      self				:			Tuple  ,	UpperCamelCase__				:			Dict      )						->			Union[str, Any]:






				"""simple docstring"""







				snake_case  :       Any     			=						d
				snake_case  :       Optional[Any]     			=						self.__dict__['''_tokenizer'''].get_vocab()
				snake_case  :       Optional[int]     			=						PreTokenizer.custom(JiebaPreTokenizer(_lowercase      )      )



		def       lowerCAmelCase				(      self				:			List[str]  ,	UpperCamelCase__				:			str  ,	UpperCamelCase__				:			int=None      )						->			int:






				"""simple docstring"""







				snake_case  :       str     			=						[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				:			List[str]  ,	UpperCamelCase__				:			List[Any]  ,	UpperCamelCase__				:			Tuple = None      )						->			List[int]:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						[self.sep_token_id]
				snake_case  :       List[Any]     			=						[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				:			Optional[int]  ,	UpperCamelCase__				:			Optional[int]  ,	UpperCamelCase__				:			int = None      )						->			Tuple[str]:






				"""simple docstring"""







				snake_case  :       Union[str, Any]     			=						self._tokenizer.model.save(_lowercase  ,	name=_lowercase      )
				return tuple(_lowercase      )



		def       lowerCAmelCase				(      self				:			Optional[int]  ,	UpperCamelCase__				:			Any  ,	UpperCamelCase__				:			Any=None  ,	UpperCamelCase__				:			Tuple=None  ,	UpperCamelCase__				:			int=False  ,	**UpperCamelCase__				:			List[str]  ,	)						->			Optional[int]:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						BertPreTokenizer()
				return super().save_pretrained(_lowercase  ,	_lowercase  ,	_lowercase  ,	_lowercase  ,	**_lowercase      )





from __future__ import annotations

import math




def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)->						int:



    """simple docstring"""






    if depth < 0:
        raise ValueError("Depth cannot be less than 0"			)

    if len(SCREAMING_SNAKE_CASE_			) == 0:
        raise ValueError("Scores cannot be empty"			)

    if depth == height:
        return scores[node_index]

    if is_max:
        return max(
            minimax(depth + 1			,						node_index * 2			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)			,						minimax(depth + 1			,						node_index * 2 + 1			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)			,						)

    return min(
        minimax(depth + 1			,						node_index * 2			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)			,						minimax(depth + 1			,						node_index * 2 + 1			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)			,						)




def 			lowerCAmelCase(      )->						None:



    """simple docstring"""






    UpperCamelCase_			  =						[9_0, 2_3, 6, 3_3, 2_1, 6_5, 1_2_3, 3_4_4_2_3]
    UpperCamelCase_			  =						math.log(len(SCREAMING_SNAKE_CASE_			)			,						2			)
    print("Optimal value : "			,						end=""			)
    print(minimax(0			,						0			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()
