





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_rembert import RemBertTokenizer
else:
		SCREAMING_SNAKE_CASE_   :      str			=   None

SCREAMING_SNAKE_CASE_   :      List[str]			=   logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_   :      Dict			=   {'''vocab_file''': '''sentencepiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

SCREAMING_SNAKE_CASE_   :      Dict			=   {
    '''vocab_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/sentencepiece.model''',
    },
    '''tokenizer_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/tokenizer.json''',
    },
}

SCREAMING_SNAKE_CASE_   :      Any			=   {
    '''google/rembert''': 256,
}

SCREAMING_SNAKE_CASE_   :      Union[str, Any]			=   '''▁'''

class 		snake_case_   (							UpperCAmelCase_						):







	'''simple docstring'''
	__UpperCamelCase   =		VOCAB_FILES_NAMES
	__UpperCamelCase   =		PRETRAINED_VOCAB_FILES_MAP
	__UpperCamelCase   =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__UpperCamelCase   =		RemBertTokenizer




	def __init__(						self							:     List[Any]					,      __lowerCamelCase							:     Union[str, Any]=None					,      __lowerCamelCase							:     Dict=None					,      __lowerCamelCase							:     Dict=True					,      __lowerCamelCase							:     Optional[Any]=True					,      __lowerCamelCase							:     Tuple=False					,      __lowerCamelCase							:     List[Any]="[CLS]"					,      __lowerCamelCase							:     int="[SEP]"					,      __lowerCamelCase							:     Union[str, Any]="<unk>"					,      __lowerCamelCase							:     List[Any]="[SEP]"					,      __lowerCamelCase							:     Tuple="<pad>"					,      __lowerCamelCase							:     str="[CLS]"					,      __lowerCamelCase							:     List[Any]="[MASK]"					,      **__lowerCamelCase							:     Dict					,      )       -> Dict:

			'''simple docstring'''




			__lowercase											=     AddedToken(__lowerCamelCase					,      lstrip=__lowerCamelCase					,      rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase					,      __lowerCamelCase   ) else mask_token

			super().__init__(
			    __lowerCamelCase					,      tokenizer_file=__lowerCamelCase					,      do_lower_case=__lowerCamelCase					,      remove_space=__lowerCamelCase					,      keep_accents=__lowerCamelCase					,      bos_token=__lowerCamelCase					,      eos_token=__lowerCamelCase					,      unk_token=__lowerCamelCase					,      sep_token=__lowerCamelCase					,      pad_token=__lowerCamelCase					,      cls_token=__lowerCamelCase					,      mask_token=__lowerCamelCase					,      **__lowerCamelCase					,      )

			__lowercase											=     do_lower_case
			__lowercase											=     remove_space
			__lowercase											=     keep_accents
			__lowercase											=     vocab_file
			__lowercase											=     False if not self.vocab_file else True




	def    UpperCAmelCase			(						self							:     Optional[Any]					,      __lowerCamelCase							:     List[int]					,      __lowerCamelCase							:     Optional[List[int]] = None   )       -> List[int]:

			'''simple docstring'''




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




	def    UpperCAmelCase			(						self							:     List[str]					,      __lowerCamelCase							:     List[int]					,      __lowerCamelCase							:     Optional[List[int]] = None					,      __lowerCamelCase							:     bool = False   )       -> List[int]:

			'''simple docstring'''




			if already_has_special_tokens:
					if token_ids_a is not None:
							raise ValueError(
							    'You should not supply a second sequence if the provided sequence of '
							    'ids is already formatted with special tokens for the model.'   )
					return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

			if token_ids_a is not None:
					return [1] + ([0] * len(__lowerCamelCase   )) + [1] + ([0] * len(__lowerCamelCase   )) + [1]
			return [1] + ([0] * len(__lowerCamelCase   )) + [1]




	def    UpperCAmelCase			(						self							:     int					,      __lowerCamelCase							:     List[int]					,      __lowerCamelCase							:     Optional[List[int]] = None   )       -> List[int]:

			'''simple docstring'''




			__lowercase											=     [self.sep_token_id]
			__lowercase											=     [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    UpperCAmelCase			(						self							:     Dict					,      __lowerCamelCase							:     str					,      __lowerCamelCase							:     Optional[str] = None   )       -> Tuple[str]:

			'''simple docstring'''




			if not os.path.isdir(__lowerCamelCase   ):
					logger.error('Vocabulary path ({}) should be a directory'.format(__lowerCamelCase   )   )
					return
			__lowercase											=     os.path.join(
			    __lowerCamelCase					,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

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

			return (out_vocab_file,)











def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case							)		->    bool:
		__lowercase											=     len(snake_case							) + 1
		__lowercase											=     len(snake_case							) + 1

		# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
		# length i of input_string matches with prefix string of length j of
		# given pattern.
		# "dp" stands for dynamic programming.
		__lowercase											=     [[0 for i in range(snake_case							)] for j in range(snake_case							)]

		# since string of zero length match pattern of zero length
		__lowercase											=     1

		# since pattern of zero length will never match with string of non-zero length
		for i in range(1						,   snake_case							):
				__lowercase											=     0

		# since string of zero length will match with pattern where there
		# is at least one * alternatively
		for j in range(1						,   snake_case							):
				__lowercase											=     dp[0][j - 2] if pattern[j - 1] == '*' else 0

		# now using bottom-up approach to find for all remaining lengths
		for i in range(1						,   snake_case							):
				for j in range(1						,   snake_case							):
						if input_string[i - 1] == pattern[j - 1] or pattern[j - 1] == ".":
								__lowercase											=     dp[i - 1][j - 1]

						elif pattern[j - 1] == "*":
								if dp[i][j - 2] == 1:
										__lowercase											=     1
								elif pattern[j - 2] in (input_string[i - 1], "."):
										__lowercase											=     dp[i - 1][j]
								else:
										__lowercase											=     0
						else:
								__lowercase											=     0

		return bool(dp[-1][-1]							)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		# inputing the strings
		# input_string = input("input a string :")
		# pattern = input("input a pattern :")

		SCREAMING_SNAKE_CASE_   :      Any			=   '''aab'''
		SCREAMING_SNAKE_CASE_   :      str			=   '''c*a*b'''

		# using function to check whether given string matches the given pattern
		if match_pattern(input_string, pattern):
				print(F"""{input_string} matches the given pattern {pattern}""")
		else:
				print(F"""{input_string} does not match with the given pattern {pattern}""")




