






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

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


UpperCamelCase    							=      logging.get_logger(__name__)

UpperCamelCase    							=      '▁'

UpperCamelCase    							=      {'vocab_file': 'prophetnet.tokenizer'}

UpperCamelCase    							=      {
    'vocab_file': {
        'microsoft/xprophetnet-large-wiki100-cased': (
            'https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/prophetnet.tokenizer'
        ),
    }
}

UpperCamelCase    							=      {
    'microsoft/xprophetnet-large-wiki100-cased': {'do_lower_case': False},
}

UpperCamelCase    							=      {
    'microsoft/xprophetnet-large-wiki100-cased': 512,
}


def 				__lowerCamelCase     (							__lowerCAmelCase							:					List[Any]							)     ->  Dict:
   __UpperCamelCase	:			int					=					collections.OrderedDict()
   with open(__lowerCAmelCase					,							"""r"""					,							encoding="""utf-8"""							) as reader:
      __UpperCamelCase	:			Optional[Any]					=					reader.readlines()
   for index, token in enumerate(__lowerCAmelCase							):
      __UpperCamelCase	:			Any					=					token.rstrip("""\n"""							)
      __UpperCamelCase	:			Optional[Any]					=					index
   return vocab







class 		_A						( UpperCAmelCase_ ):
  lowercase_						:			Union[str, Any]						=					VOCAB_FILES_NAMES
  lowercase_						:			Union[str, Any]						=					PRETRAINED_VOCAB_FILES_MAP
  lowercase_						:			str						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowercase_						:			Optional[int]						=					['''input_ids''', '''attention_mask''']

  def __init__(    self						:	List[str]   ,				lowerCamelCase__						:	Optional[Any]   ,				lowerCamelCase__						:	str="[SEP]"   ,				lowerCamelCase__						:	Tuple="[SEP]"   ,				lowerCamelCase__						:	Dict="[SEP]"   ,				lowerCamelCase__						:	Union[str, Any]="[UNK]"   ,				lowerCamelCase__						:	Any="[PAD]"   ,				lowerCamelCase__						:	List[str]="[CLS]"   ,				lowerCamelCase__						:	Union[str, Any]="[MASK]"   ,				lowerCamelCase__						:	Optional[Dict[str, Any]] = None   ,				**lowerCamelCase__						:	Tuple   ,				):
     """simple docstring"""

     __UpperCamelCase	:			str					=					{} if sp_model_kwargs is None else sp_model_kwargs

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

     try:
        import sentencepiece as spm
     except ImportError:
        logger.warning(
            """You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece"""
            """ pip install sentencepiece"""			)
        raise

     __UpperCamelCase	:			Optional[Any]					=					spm.SentencePieceProcessor(**self.sp_model_kwargs			)
     self.sp_model.Load(str(lowerCamelCase__			)			)
     __UpperCamelCase	:			Union[str, Any]					=					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'

     # put special tokens and [unused] tokens into the vocab
     __UpperCamelCase	:			Tuple					=					{"""[PAD]""": 0, """[CLS]""": 1, """[SEP]""": 2, """[UNK]""": 3, """[MASK]""": 4}

     for i in range(10			):
        __UpperCamelCase	:			Union[str, Any]					=					f'[unused{i}]'
        __UpperCamelCase	:			str					=					5 + i

     # The first "real" token "," has position 15 in the embedding vocab and position 3 in the spm vocab
     __UpperCamelCase	:			int					=					12
     __UpperCamelCase	:			List[str]					=					{v: k for k, v in self.fairseq_tokens_to_ids.items()}
     for k in self.fairseq_tokens_to_ids.keys():
        self.unique_no_split_tokens.append(lowerCamelCase__			)

  def __getstate__(    self						:	Tuple			):
     """simple docstring"""

     __UpperCamelCase	:			List[Any]					=					self.__dict__.copy()
     __UpperCamelCase	:			List[str]					=					None
     return state

  def __setstate__(    self						:	List[str]   ,				lowerCamelCase__						:	Dict			):
     """simple docstring"""

     __UpperCamelCase	:			Dict					=					d
     try:
        import sentencepiece as spm
     except ImportError:
        logger.warning(
            """You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece"""
            """ pip install sentencepiece"""			)
        raise

     # for backward compatibility
     if not hasattr(self   ,				"""sp_model_kwargs"""			):
        __UpperCamelCase	:			List[str]					=					{}

     __UpperCamelCase	:			List[str]					=					spm.SentencePieceProcessor(**self.sp_model_kwargs			)
     self.sp_model.Load(self.vocab_file			)

  def    a					(    self						:	str   ,				lowerCamelCase__						:	List[int]   ,				lowerCamelCase__						:	Optional[List[int]] = None   ,				lowerCamelCase__						:	bool = False			):
     """simple docstring"""

     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 ([0] * len(lowerCamelCase__			)) + [1]
     return ([0] * len(lowerCamelCase__			)) + [1] + ([0] * len(lowerCamelCase__			)) + [1]

  def    a					(    self						:	Any   ,				lowerCamelCase__						:	List[int]   ,				lowerCamelCase__						:	Optional[List[int]] = None			):
     """simple docstring"""

     __UpperCamelCase	:			Union[str, Any]					=					[self.sep_token_id]

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

  @property
  def    a					(    self						:	List[str]			):
     """simple docstring"""

     return len(self.sp_model			) + self.fairseq_offset

  def    a					(    self						:	Union[str, Any]			):
     """simple docstring"""

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

  def    a					(    self						:	int   ,				lowerCamelCase__						:	str			):
     """simple docstring"""

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

  def    a					(    self						:	List[Any]   ,				lowerCamelCase__						:	Optional[Any]			):
     """simple docstring"""

     if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
     __UpperCamelCase	:			Dict					=					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    a					(    self						:	Union[str, Any]   ,				lowerCamelCase__						:	Optional[Any]			):
     """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    a					(    self						:	Dict   ,				lowerCamelCase__						:	List[str]			):
     """simple docstring"""

     __UpperCamelCase	:			Any					=					"""""".join(lowerCamelCase__			).replace(lowerCamelCase__   ,				""" """			).strip()
     return out_string

  def    a					(    self						:	Dict   ,				lowerCamelCase__						:	str   ,				lowerCamelCase__						:	Optional[str] = None			):
     """simple docstring"""

     if not os.path.isdir(lowerCamelCase__			):
        logger.error(f'Vocabulary path ({save_directory}) should be a directory'			)
        return
     __UpperCamelCase	:			Optional[Any]					=					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:
           __UpperCamelCase	:			Tuple					=					self.sp_model.serialized_model_proto()
           fi.write(lowerCamelCase__			)

     return (out_vocab_file,)

  def    a					(    self						:	List[str]   ,				lowerCamelCase__						:	List[int]   ,				lowerCamelCase__						:	Optional[List[int]] = None			):
     """simple docstring"""

     if token_ids_a is None:
        return token_ids_a + [self.sep_token_id]
     __UpperCamelCase	:			List[Any]					=					[self.sep_token_id]
     return token_ids_a + sep + token_ids_a + sep











from __future__ import annotations







class 		_A						:

  def __init__(    self						:	List[str]   ,				lowerCamelCase__						:	Any=None			):
     """simple docstring"""

     __UpperCamelCase	:			Union[str, Any]					=					data
     __UpperCamelCase	:			Union[str, Any]					=					None

  def __repr__(    self						:	int			):
     """simple docstring"""

     __UpperCamelCase	:			Union[str, Any]					=					[]
     __UpperCamelCase	:			Optional[int]					=					self
     while temp:
        string_rep.append(f'{temp.data}'			)
        __UpperCamelCase	:			Dict					=					temp.next
     return "->".join(lowerCamelCase__			)







def 				__lowerCamelCase     (							__lowerCAmelCase							:					list							)     ->  Tuple:
   if not elements_list:
      raise Exception("""The Elements List is empty"""							)

   __UpperCamelCase	:			Dict					=					Node(elements_list[0]							)
   for i in range(1					,							len(__lowerCAmelCase							)							):
      __UpperCamelCase	:			List[str]					=					Node(elements_list[i]							)
      __UpperCamelCase	:			Optional[int]					=					current.next
   return head


def 				__lowerCamelCase     (							__lowerCAmelCase							:					Node							)     ->  None:
   if head_node is not None and isinstance(__lowerCAmelCase					,							__lowerCAmelCase							):
      print_reverse(head_node.next							)
      print(head_node.data							)


def 				__lowerCamelCase     (							)     ->  Union[str, Any]:
   from doctest import testmod

   testmod()

   __UpperCamelCase	:			Any					=					make_linked_list([14, 52, 14, 12, 43]							)
   print("""Linked List:"""							)
   print(__lowerCAmelCase							)
   print("""Elements in Reverse:"""							)
   print_reverse(__lowerCAmelCase							)


if __name__ == "__main__":
       main()



