


"""simple docstring"""


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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A_      =    logging.get_logger(__name__)

A_      =    """▁"""

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

A_      =    {
    """vocab_file""": {
        """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model""",
    }
}

A_      =    {
    """facebook/xglm-564M""": 20_48,
}






class  lowercase(					__a			):







 '''simple docstring'''





 lowercase__			 = VOCAB_FILES_NAMES
 lowercase__			 = PRETRAINED_VOCAB_FILES_MAP
 lowercase__			 = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase__			 = ["input_ids", "attention_mask"]


 def __init__(    self:		int,				a_:		Optional[int],				a_:		str="<s>",				a_:		Optional[Any]="</s>",				a_:		Optional[int]="</s>",				a_:		List[Any]="<s>",				a_:		Tuple="<unk>",				a_:		List[str]="<pad>",				a_:		Optional[Dict[str, Any]] = None,				**a_:		List[Any],				):




   '''simple docstring'''



   _snake_case							:		Optional[int]								=  {} if sp_model_kwargs is None else sp_model_kwargs

   # Compatibility with the original tokenizer
   _snake_case							:		Union[str, Any]								=  7
   _snake_case							:		int								=  [f"<madeupword{i}>" for i in range(self.num_madeup_words		)]

   _snake_case							:		Optional[int]								=  kwargs.get("""additional_special_tokens""",				[]		)
   kwargs["additional_special_tokens"] += [
       word for word in madeup_words if word not in kwargs["additional_special_tokens"]
   ]

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

   _snake_case							:		str								=  spm.SentencePieceProcessor(**self.sp_model_kwargs		)
   self.sp_model.Load(str(a_		)		)
   _snake_case							:		Optional[int]								=  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'

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

   # Mimic fairseq token-to-id alignment for the first 4 token
   _snake_case							:		List[Any]								=  {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

   _snake_case							:		List[Any]								=  len(self.sp_model		)
   _snake_case							:		List[str]								=  {f"<madeupword{i}>": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words		)}
   self.fairseq_tokens_to_ids.update(a_		)

   _snake_case							:		List[str]								=  {v: k for k, v in self.fairseq_tokens_to_ids.items()}


 def __getstate__(    self:		Tuple		):




   '''simple docstring'''



   _snake_case							:		Union[str, Any]								=  self.__dict__.copy()
   _snake_case							:		str								=  None
   _snake_case							:		List[Any]								=  self.sp_model.serialized_model_proto()
   return state


 def __setstate__(    self:		Optional[Any],				a_:		Optional[int]		):




   '''simple docstring'''



   _snake_case							:		List[Any]								=  d

   # for backward compatibility
   if not hasattr(self,				"""sp_model_kwargs"""		):
     _snake_case							:		str								=  {}

   _snake_case							:		Any								=  spm.SentencePieceProcessor(**self.sp_model_kwargs		)
   self.sp_model.LoadFromSerializedProto(self.sp_model_proto		)


 def 			UpperCamelCase_       (    self:		Any,				a_:		List[int],				a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   if token_ids_a is None:
     return [self.sep_token_id] + token_ids_a
   _snake_case							:		Union[str, Any]								=  [self.sep_token_id]
   return sep + token_ids_a + sep + sep + token_ids_a


 def 			UpperCamelCase_       (    self:		Dict,				a_:		List[int],				a_:		Optional[List[int]] = None,				a_:		bool = False		):




   '''simple docstring'''



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

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


 def 			UpperCamelCase_       (    self:		Tuple,				a_:		List[int],				a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   _snake_case							:		str								=  [self.sep_token_id]

   if token_ids_a is None:
     return len(sep + token_ids_a		) * [0]
   return len(sep + token_ids_a + sep + sep + token_ids_a		) * [0]


 @property
 def 			UpperCamelCase_       (    self:		int		):




   '''simple docstring'''



   return len(self.sp_model		) + self.fairseq_offset + self.num_madeup_words


 def 			UpperCamelCase_       (    self:		str		):




   '''simple docstring'''



   _snake_case							:		List[str]								=  {self.convert_ids_to_tokens(a_		): i for i in range(self.vocab_size		)}
   vocab.update(self.added_tokens_encoder		)
   return vocab


 def 			UpperCamelCase_       (    self:		str,				a_:		str		):




   '''simple docstring'''



   return self.sp_model.encode(a_,				out_type=a_		)


 def 			UpperCamelCase_       (    self:		Optional[Any],				a_:		Optional[int]		):




   '''simple docstring'''



   if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
   _snake_case							:		List[str]								=  self.sp_model.PieceToId(a_		)

   # 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 			UpperCamelCase_       (    self:		int,				a_:		int		):




   '''simple docstring'''



   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 			UpperCamelCase_       (    self:		Optional[int],				a_:		List[str]		):




   '''simple docstring'''



   _snake_case							:		List[str]								=  """""".join(a_		).replace(a_,				""" """		).strip()
   return out_string


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




   '''simple docstring'''



   if not os.path.isdir(a_		):
     logger.error(f"Vocabulary path ({save_directory}) should be a directory"		)
     return
   _snake_case							:		int								=  os.path.join(
       a_,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)

   if os.path.abspath(self.vocab_file		) != os.path.abspath(a_		) and os.path.isfile(self.vocab_file		):
     copyfile(self.vocab_file,				a_		)
   elif not os.path.isfile(self.vocab_file		):
     with open(a_,				"""wb"""		) as fi:
       _snake_case							:		Optional[int]								=  self.sp_model.serialized_model_proto()
       fi.write(a_		)

   return (out_vocab_file,)








"""simple docstring"""


from typing import Any






class  lowercase:







 '''simple docstring'''





 def __init__(    self:		Dict,				a_:		Any		):




   '''simple docstring'''



   _snake_case							:		Dict								=  data
   _snake_case							:		Optional[Any]								=  None







class  lowercase:







 '''simple docstring'''





 def __init__(    self:		str		):




   '''simple docstring'''



   _snake_case							:		Any								=  None


 def 			UpperCamelCase_       (    self:		Any		):




   '''simple docstring'''



   _snake_case							:		List[Any]								=  self.head
   while temp is not None:
     print(temp.data,				end=""" """		)
     _snake_case							:		int								=  temp.next
   print()


 def 			UpperCamelCase_       (    self:		Union[str, Any],				a_:		Any		):




   '''simple docstring'''



   _snake_case							:		Optional[Any]								=  Node(a_		)
   _snake_case							:		Union[str, Any]								=  self.head
   _snake_case							:		List[Any]								=  new_node


 def 			UpperCamelCase_       (    self:		Tuple,				a_:		List[str],				a_:		Union[str, Any]		):




   '''simple docstring'''



   if node_data_a == node_data_a:
     return
   else:
     _snake_case							:		int								=  self.head
     while node_a is not None and node_a.data != node_data_a:
       _snake_case							:		List[Any]								=  node_a.next

     _snake_case							:		List[Any]								=  self.head
     while node_a is not None and node_a.data != node_data_a:
       _snake_case							:		List[Any]								=  node_a.next

     if node_a is None or node_a is None:
       return

     _snake_case		, _snake_case							:		int								=  node_a.data, node_a.data


if __name__ == "__main__":
     A_      =    LinkedList()
     for i in range(5, 0, -1):
          ll.push(i)

     ll.print_list()

     ll.swap_nodes(1, 4)
     print('''After swapping''')
     ll.print_list()


