

'''simple docstring'''
import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin


class    a__  (							lowerCamelCase_  ,      unittest.TestCase  ):
   _SCREAMING_SNAKE_CASE    :     Dict	       =							PhobertTokenizer
   _SCREAMING_SNAKE_CASE    :     str	       =							False


   def 						_lowerCamelCase   ( self  ):





      """simple docstring"""





      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      _lowercase			:      str			     =   ["T@@", "i", "I", "R@@", "r", "e@@"]
      _lowercase			:      Optional[Any]			     =   dict(zip(A_			,				range(len(A_  )  )  )  )
      _lowercase			:      Optional[Any]			     =   ["#version: 0.2", "l à</w>"]
      _lowercase			:      Optional[int]			     =   {"unk_token": "<unk>"}

      _lowercase			:      List[Any]			     =   os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES["vocab_file"]  )
      _lowercase			:      Tuple			     =   os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES["merges_file"]  )

      with open(self.vocab_file			,				"w"			,				encoding="utf-8"  ) as fp:
         for token in vocab_tokens:
            fp.write(f'''{token} {vocab_tokens[token]}\n'''  )
      with open(self.merges_file			,				"w"			,				encoding="utf-8"  ) as fp:
         fp.write("\n".join(A_  )  )


   def 						_lowerCamelCase   ( self			,				**_UpperCamelCase  ):





      """simple docstring"""





      kwargs.update(self.special_tokens_map  )
      return PhobertTokenizer.from_pretrained(self.tmpdirname			,				**A_  )


   def 						_lowerCamelCase   ( self			,				_UpperCamelCase  ):





      """simple docstring"""





      _lowercase			:      Union[str, Any]			     =   "Tôi là VinAI Research"
      _lowercase			:      Optional[Any]			     =   "T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
      return input_text, output_text






   def 						_lowerCamelCase   ( self  ):





      """simple docstring"""





      _lowercase			:      List[Any]			     =   PhobertTokenizer(self.vocab_file			,				self.merges_file			,				**self.special_tokens_map  )
      _lowercase			:      List[Any]			     =   "Tôi là VinAI Research"
      _lowercase			:      str			     =   "T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
      _lowercase			:      List[str]			     =   tokenizer.tokenize(A_  )
      print(A_  )
      self.assertListEqual(A_			,				A_  )

      _lowercase			:      str			     =   tokens + [tokenizer.unk_token]

      _lowercase			:      str			     =   [4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A_  )			,				A_  )












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_fnet import FNetTokenizer
else:
 lowerCamelCase				:		List[Any]     =   None

lowerCamelCase				:		int     =   logging.get_logger(__name__)
lowerCamelCase				:		Optional[int]     =   {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase				:		Optional[int]     =   {
    "vocab_file": {
        "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/spiece.model",
        "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/spiece.model",
    },
    "tokenizer_file": {
        "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json",
        "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json",
    },
}

lowerCamelCase				:		List[Any]     =   {
    "google/fnet-base": 512,
    "google/fnet-large": 512,
}

lowerCamelCase				:		Any     =   "▁"







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 UpperCamelCase						   =						VOCAB_FILES_NAMES
 UpperCamelCase						   =						PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase						   =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCamelCase						   =						['''input_ids''', '''token_type_ids''']
 UpperCamelCase						   =						FNetTokenizer

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

       """simple docstring"""






       lowerCamelCase_		     =    (
           AddedToken(A_						,							lstrip=A_						,							rstrip=A_						,							normalized=A_  )
           if isinstance(A_						,							A_  )
           else mask_token
       )

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

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

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

       """simple docstring"""






       lowerCamelCase_		     =    [self.sep_token_id]
       lowerCamelCase_		     =    [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 				a__ (				self					:  Tuple						,							A_					:  List[int]						,							A_					:  Optional[List[int]] = None  )   ->	List[int]:

       """simple docstring"""






       lowerCamelCase_		     =    [self.sep_token_id]
       lowerCamelCase_		     =    [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 				a__ (				self					:  Dict						,							A_					:  str						,							A_					:  Optional[str] = None  )   ->	Tuple[str]:

       """simple docstring"""






       if not os.path.isdir(A_  ):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
             return
       lowerCamelCase_		     =    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_  ):
             copyfile(self.vocab_file						,							A_  )

       return (out_vocab_file,)



