




'''simple docstring'''


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_lowercase  =			logging.get_logger(__name__)

_lowercase  =			"""▁"""

_lowercase  =			{"""vocab_file""": """sentencepiece.bpe.model"""}

_lowercase  =			{
    """vocab_file""": {
        """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large-finetuned-conll02-dutch""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll02-spanish""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-english""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-german""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

_lowercase  =			{
    """xlm-roberta-base""": 5_12,
    """xlm-roberta-large""": 5_12,
    """xlm-roberta-large-finetuned-conll02-dutch""": 5_12,
    """xlm-roberta-large-finetuned-conll02-spanish""": 5_12,
    """xlm-roberta-large-finetuned-conll03-english""": 5_12,
    """xlm-roberta-large-finetuned-conll03-german""": 5_12,
}
class 						a_				(			_lowerCAmelCase						):
	lowercase_       :     Any			  =      VOCAB_FILES_NAMES
	lowercase_       :     str			  =      PRETRAINED_VOCAB_FILES_MAP
	lowercase_       :     Any			  =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowercase_       :     Dict			  =      ['''input_ids''', '''attention_mask''']




	def __init__(       self     :  str       ,		__lowerCAmelCase     :  str       ,		__lowerCAmelCase     :  str="<s>"       ,		__lowerCAmelCase     :  Tuple="</s>"       ,		__lowerCAmelCase     :  Union[str, Any]="</s>"       ,		__lowerCAmelCase     :  Union[str, Any]="<s>"       ,		__lowerCAmelCase     :  str="<unk>"       ,		__lowerCAmelCase     :  int="<pad>"       ,		__lowerCAmelCase     :  Any="<mask>"       ,		__lowerCAmelCase     :  List[str] = None       ,		**__lowerCAmelCase     :  List[str]       ,		):
							__snake_case						 =   AddedToken(__lowerCAmelCase       ,		lstrip=__lowerCAmelCase       ,		rstrip=__lowerCAmelCase      ) if isinstance(__lowerCAmelCase       ,		__lowerCAmelCase      ) else mask_token

							__snake_case						 =   {} if sp_model_kwargs is None else sp_model_kwargs

							super().__init__(
							    bos_token=__lowerCAmelCase       ,		eos_token=__lowerCAmelCase       ,		unk_token=__lowerCAmelCase       ,		sep_token=__lowerCAmelCase       ,		cls_token=__lowerCAmelCase       ,		pad_token=__lowerCAmelCase       ,		mask_token=__lowerCAmelCase       ,		sp_model_kwargs=self.sp_model_kwargs       ,		**__lowerCAmelCase       ,		)

							__snake_case						 =   spm.SentencePieceProcessor(**self.sp_model_kwargs      )
							self.sp_model.Load(str(__lowerCAmelCase      )      )
							__snake_case						 =   vocab_file

							# Original fairseq vocab and spm vocab must be "aligned":
							# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
							# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
							# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
							# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

							# Mimic fairseq token-to-id alignment for the first 4 token
							__snake_case						 =   {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

							# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
							__snake_case						 =   1

							__snake_case						 =   len(self.sp_model      ) + self.fairseq_offset
							__snake_case						 =   {v: k for k, v in self.fairseq_tokens_to_ids.items()}




	def __getstate__(       self     :  Optional[int]      ):
							__snake_case						 =   self.__dict__.copy()
							__snake_case						 =   None
							__snake_case						 =   self.sp_model.serialized_model_proto()
							return state




	def __setstate__(       self     :  Dict       ,		__lowerCAmelCase     :  List[Any]      ):
							__snake_case						 =   d

							# for backward compatibility
							if not hasattr(self       ,		'sp_model_kwargs'      ):
													__snake_case						 =   {}

							__snake_case						 =   spm.SentencePieceProcessor(**self.sp_model_kwargs      )
							self.sp_model.LoadFromSerializedProto(self.sp_model_proto      )




	def   lowercase__   (       self     :  Dict       ,		__lowerCAmelCase     :  Optional[int]       ,		__lowerCAmelCase     :  str = None      ):

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




	def   lowercase__   (       self     :  Any       ,		__lowerCAmelCase     :  int       ,		__lowerCAmelCase     :  Optional[int] = None       ,		__lowerCAmelCase     :  str = False      ):

							if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=__lowerCAmelCase       ,		token_ids_a=__lowerCAmelCase       ,		already_has_special_tokens=__lowerCAmelCase      )

							if token_ids_a is None:
													return [1] + ([0] * len(__lowerCAmelCase      )) + [1]
							return [1] + ([0] * len(__lowerCAmelCase      )) + [1, 1] + ([0] * len(__lowerCAmelCase      )) + [1]




	def   lowercase__   (       self     :  List[str]       ,		__lowerCAmelCase     :  Dict       ,		__lowerCAmelCase     :  Union[str, Any] = None      ):
							__snake_case						 =   [self.sep_token_id]
							__snake_case						 =   [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 + sep + token_ids_a + sep      ) * [0]




	@property
	def   lowercase__   (       self     :  Union[str, Any]      ):
							return len(self.sp_model      ) + self.fairseq_offset + 1  # Add the <mask> token




	def   lowercase__   (       self     :  Tuple      ):
							__snake_case						 =   {self.convert_ids_to_tokens(__lowerCAmelCase      ): i for i in range(self.vocab_size      )}
							vocab.update(self.added_tokens_encoder      )
							return vocab




	def   lowercase__   (       self     :  List[Any]       ,		__lowerCAmelCase     :  str      ):
							return self.sp_model.encode(__lowerCAmelCase       ,		out_type=__lowerCAmelCase      )




	def   lowercase__   (       self     :  Tuple       ,		__lowerCAmelCase     :  List[Any]      ):
							if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
							__snake_case						 =   self.sp_model.PieceToId(__lowerCAmelCase      )

							# Need to return unknown token if the SP model returned 0
							return spm_id + self.fairseq_offset if spm_id else self.unk_token_id




	def   lowercase__   (       self     :  str       ,		__lowerCAmelCase     :  Tuple      ):
							if index in self.fairseq_ids_to_tokens:
													return self.fairseq_ids_to_tokens[index]
							return self.sp_model.IdToPiece(index - self.fairseq_offset      )




	def   lowercase__   (       self     :  Tuple       ,		__lowerCAmelCase     :  List[str]      ):
							__snake_case						 =   ''.join(__lowerCAmelCase      ).replace(__lowerCAmelCase       ,		' '      ).strip()
							return out_string




	def   lowercase__   (       self     :  Tuple       ,		__lowerCAmelCase     :  Optional[Any]       ,		__lowerCAmelCase     :  Dict = None      ):
							if not os.path.isdir(__lowerCAmelCase      ):
													logger.error(F'Vocabulary path ({save_directory}) should be a directory'      )
													return
							__snake_case						 =   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      ) and os.path.isfile(self.vocab_file      ):
													copyfile(self.vocab_file       ,		__lowerCAmelCase      )
							elif not os.path.isfile(self.vocab_file      ):
													with open(__lowerCAmelCase       ,		'wb'      ) as fi:
																			__snake_case						 =   self.sp_model.serialized_model_proto()
																			fi.write(__lowerCAmelCase      )

							return (out_vocab_file,)









'''simple docstring'''



from timeit import timeit

__UpperCamelCase   :							int         =   {
    """MALAYALAM""": True,
    """String""": False,
    """rotor""": True,
    """level""": True,
    """A""": True,
    """BB""": True,
    """ABC""": False,
    """amanaplanacanalpanama""": True,  # "a man a plan a canal panama"
}
# Ensure our test data is valid
assert all((key == key[::-1]) is value for key, value in test_data.items())



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str     )	->      bool:

   """simple docstring"""
   __a					  =     0
   __a					  =     len(SCREAMING_SNAKE_CASE__     ) - 1
   while start_i < end_i:
      if s[start_i] == s[end_i]:
         start_i += 1
         end_i -= 1
      else:
         return False
   return True



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str     )	->      bool:

   """simple docstring"""
   __a					  =     len(SCREAMING_SNAKE_CASE__     ) // 2
   __a					  =     len(SCREAMING_SNAKE_CASE__     )

   # We need to traverse till half of the length of string
   # as we can get access of the i'th last element from
   # i'th index.
   # eg: [0,1,2,3,4,5] => 4th index can be accessed
   # with the help of 1st index (i==n-i-1)
   # where n is length of string
   return all(s[i] == s[n - i - 1] for i in range(SCREAMING_SNAKE_CASE__     )     )



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str     )	->      bool:

   """simple docstring"""
   if len(SCREAMING_SNAKE_CASE__     ) <= 2:
      return True
   if s[0] == s[len(SCREAMING_SNAKE_CASE__     ) - 1]:
      return is_palindrome_recursive(s[1:-1]     )
   else:
      return False



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str     )	->      bool:

   """simple docstring"""
   return s == s[::-1]



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str     )	->      None:

   """simple docstring"""
   __a					  =     f"""all({name}(key) is value for key, value in test_data.items())"""
   __a					  =     f"""from __main__ import test_data, {name}"""
   __a					  =     500000
   __a					  =     timeit(stmt=SCREAMING_SNAKE_CASE__,       setup=SCREAMING_SNAKE_CASE__,       number=SCREAMING_SNAKE_CASE__     )
   print(f"""{name:<35} finished {number:,} runs in {result:.5f} seconds"""     )


if __name__ == "__main__":
 for key, value in test_data.items():
  assert is_palindrome(key) is is_palindrome_recursive(key)
  assert is_palindrome(key) is is_palindrome_slice(key)
  print(f"""{key:21} {value}""")
 print("""a man a plan a canal panama""")

 # finished 500,000 runs in 0.46793 seconds
 benchmark_function("""is_palindrome_slice""")
 # finished 500,000 runs in 0.85234 seconds
 benchmark_function("""is_palindrome""")
 # finished 500,000 runs in 1.32028 seconds
 benchmark_function("""is_palindrome_recursive""")
 # finished 500,000 runs in 2.08679 seconds
 benchmark_function("""is_palindrome_traversal""")