

"""simple docstring"""



from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_openai import OpenAIGPTTokenizer


SCREAMING_SNAKE_CASE_       :						int					=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_       :						Optional[Any]					=    {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

SCREAMING_SNAKE_CASE_       :						Tuple					=    {
    '''vocab_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/vocab.json'''},
    '''merges_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/merges.txt'''},
    '''tokenizer_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/tokenizer.json'''},
}

SCREAMING_SNAKE_CASE_       :						int					=    {
    '''openai-gpt''': 5_1_2,
}



class        a    (							_lowercase					):



    """simple docstring"""



    UpperCAmelCase    			=       VOCAB_FILES_NAMES
    UpperCAmelCase    			=       PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase    			=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase    			=       ["input_ids", "attention_mask"]
    UpperCAmelCase    			=       OpenAIGPTTokenizer

    def __init__(  self:			Optional[int]     ,    UpperCamelCase:			Any=None     ,    UpperCamelCase:			Optional[int]=None     ,    UpperCamelCase:			List[Any]=None     ,    UpperCamelCase:			List[Any]="<unk>"     ,    **UpperCamelCase:			Tuple							):






         """simple docstring"""


         super().__init__(__SCREAMING_SNAKE_CASE     ,    __SCREAMING_SNAKE_CASE     ,    tokenizer_file=__SCREAMING_SNAKE_CASE     ,    unk_token=__SCREAMING_SNAKE_CASE     ,    **__SCREAMING_SNAKE_CASE							)

    @property
    def 					UpperCamelCase						(  self:			Optional[Any]							):






         """simple docstring"""


         return True





    def 					UpperCamelCase						(  self:			int     ,    UpperCamelCase:			str     ,    UpperCamelCase:			Optional[str] = None							):






         """simple docstring"""


         A__				      =	self._tokenizer.model.save(__SCREAMING_SNAKE_CASE     ,    name=__SCREAMING_SNAKE_CASE							)
         return tuple(__SCREAMING_SNAKE_CASE							)







def  UpperCAmelCase__(    lowerCamelCase_	):



			"""simple docstring"""





			_snake_case														=   len(lowerCamelCase_	)
			_snake_case														=   [0] * length
			_snake_case														=   [[False for i in range(lowerCamelCase_	)] for j in range(lowerCamelCase_	)]
			for i, c in enumerate(lowerCamelCase_	):
						_snake_case														=   i
						for j in range(i + 1	):
									if c == string[j] and (i - j < 2 or is_palindromic[j + 1][i - 1]):
												_snake_case														=   True
												_snake_case														=   min(lowerCamelCase_				,						0 if j == 0 else (cut[j - 1] + 1)	)
						_snake_case														=   mincut
			return cut[length - 1]


if __name__ == "__main__":
			_SCREAMING_SNAKE_CASE:    Dict     						=							input('''Enter the string: ''').strip()
			_SCREAMING_SNAKE_CASE:    str     						=							find_minimum_partitions(s)
			print(F"Minimum number of partitions required for the '{s}' is {ans}")

