
"""simple docstring"""






import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__SCREAMING_SNAKE_CASE							=     get_tests_dir('fixtures/spiece.model')





@require_sentencepiece
@require_tokenizers
class 				a__					(						_a   ,							unittest.TestCase       ):
     UpperCAmelCase__         =      AlbertTokenizer
     UpperCAmelCase__         =      AlbertTokenizerFast
     UpperCAmelCase__         =      True
     UpperCAmelCase__         =      True
     UpperCAmelCase__         =      True



     def  lowerCamelCase_						(							self :Dict   ):







      '''simple docstring'''



      super().setUp()

      # We have a SentencePiece fixture for testing
      UpperCamelCase_     :					Dict   	=AlbertTokenizer(__lowerCamelCase   )
      tokenizer.save_pretrained(self.tmpdirname   )



     def  lowerCamelCase_						(							self :Any      ,  _lowerCamelCase :Union[str, Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Tuple   	='this is a test'
      UpperCamelCase_     :					Optional[Any]   	='this is a test'
      return input_text, output_text



     def  lowerCamelCase_						(							self :Any   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	='<pad>'
      UpperCamelCase_     :					str   	=0

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCamelCase   )      ,  __lowerCamelCase   )
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCamelCase   )      ,  __lowerCamelCase   )



     def  lowerCamelCase_						(							self :Optional[int]   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[str]   	=list(self.get_tokenizer().get_vocab().keys()   )

      self.assertEqual(vocab_keys[0]      ,  '<pad>'   )
      self.assertEqual(vocab_keys[1]      ,  '<unk>'   )
      self.assertEqual(vocab_keys[-1]      ,  '▁eloquent'   )
      self.assertEqual(len(__lowerCamelCase   )      ,  30_000   )



     def  lowerCamelCase_						(							self :Union[str, Any]   ):







      '''simple docstring'''



      self.assertEqual(self.get_tokenizer().vocab_size      ,  30_000   )



     def  lowerCamelCase_						(							self :str   ):







      '''simple docstring'''



      if not self.test_rust_tokenizer:
       return

      UpperCamelCase_     :					Tuple   	=self.get_tokenizer()
      UpperCamelCase_     :					Union[str, Any]   	=self.get_rust_tokenizer()

      UpperCamelCase_     :					Union[str, Any]   	='I was born in 92000, and this is falsé.'

      UpperCamelCase_     :					Optional[int]   	=tokenizer.tokenize(__lowerCamelCase   )
      UpperCamelCase_     :					List[Any]   	=rust_tokenizer.tokenize(__lowerCamelCase   )
      self.assertListEqual(__lowerCamelCase      ,  __lowerCamelCase   )

      UpperCamelCase_     :					Tuple   	=tokenizer.encode(__lowerCamelCase      ,  add_special_tokens=__lowerCamelCase   )
      UpperCamelCase_     :					int   	=rust_tokenizer.encode(__lowerCamelCase      ,  add_special_tokens=__lowerCamelCase   )
      self.assertListEqual(__lowerCamelCase      ,  __lowerCamelCase   )

      UpperCamelCase_     :					List[str]   	=self.get_rust_tokenizer()
      UpperCamelCase_     :					Optional[Any]   	=tokenizer.encode(__lowerCamelCase   )
      UpperCamelCase_     :					Dict   	=rust_tokenizer.encode(__lowerCamelCase   )
      self.assertListEqual(__lowerCamelCase      ,  __lowerCamelCase   )



     def  lowerCamelCase_						(							self :Dict   ):







      '''simple docstring'''



      UpperCamelCase_     :					Tuple   	=AlbertTokenizer(__lowerCamelCase      ,  keep_accents=__lowerCamelCase   )

      UpperCamelCase_     :					Tuple   	=tokenizer.tokenize('This is a test'   )
      self.assertListEqual(__lowerCamelCase      ,  ['▁this', '▁is', '▁a', '▁test']   )

      self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase   )      ,  [48, 25, 21, 1_289]   )

      UpperCamelCase_     :					Tuple   	=tokenizer.tokenize('I was born in 92000, and this is falsé.'   )
      self.assertListEqual(
          __lowerCamelCase      ,  ['▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.']   )
      UpperCamelCase_     :					int   	=tokenizer.convert_tokens_to_ids(__lowerCamelCase   )
      self.assertListEqual(__lowerCamelCase      ,  [31, 23, 386, 19, 561, 3_050, 15, 17, 48, 25, 8_256, 18, 1, 9]   )

      UpperCamelCase_     :					List[str]   	=tokenizer.convert_ids_to_tokens(__lowerCamelCase   )
      self.assertListEqual(
          __lowerCamelCase      ,  ['▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.']      ,  )



     def  lowerCamelCase_						(							self :Tuple   ):







      '''simple docstring'''



      UpperCamelCase_     :					Dict   	=AlbertTokenizer(__lowerCamelCase   )

      UpperCamelCase_     :					str   	=tokenizer.encode('sequence builders'   )
      UpperCamelCase_     :					Tuple   	=tokenizer.encode('multi-sequence build'   )

      UpperCamelCase_     :					Dict   	=tokenizer.build_inputs_with_special_tokens(__lowerCamelCase   )
      UpperCamelCase_     :					Union[str, Any]   	=tokenizer.build_inputs_with_special_tokens(__lowerCamelCase      ,  __lowerCamelCase   )

      assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
      assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
          tokenizer.sep_token_id
      ]




     @slow
     def  lowerCamelCase_						(							self :List[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Tuple   	={'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'input_ids': [[2, 21_970, 13, 5, 6_092, 167, 28, 7_103, 2_153, 673, 8, 7_028, 12_051, 18, 17, 7_103, 2_153, 673, 8, 3_515, 18_684, 8, 4_461, 6, 1_927, 297, 8, 12_060, 2_607, 18, 13, 5, 4_461, 15, 10_538, 38, 8, 135, 15, 822, 58, 15, 993, 10_363, 15, 1_460, 8_005, 4_461, 15, 993, 255, 2_328, 9, 9, 9, 6, 26, 1_112, 816, 3_260, 13, 5, 103, 2_377, 6, 17, 1_112, 816, 2_782, 13, 5, 103, 10_641, 6, 29, 84, 2_512, 2_430, 782, 18_684, 2_761, 19, 808, 2_430, 2_556, 17, 855, 1_480, 9_477, 4_091, 128, 11_712, 15, 7_103, 2_153, 673, 17, 24_883, 9_990, 9, 3], [2, 11_502, 25, 1_006, 20, 782, 8, 11_809, 855, 1_732, 19_393, 18_667, 37, 367, 21_018, 69, 1_854, 34, 11_860, 19_124, 27, 156, 225, 17, 193, 4_141, 19, 65, 9_124, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 14, 2_231, 886, 2_385, 17_659, 84, 14, 16_792, 1_952, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
      # fmt: on

      self.tokenizer_integration_test_util(
          expected_encoding=__lowerCamelCase      ,  model_name='albert-base-v2'      ,  revision='6b6560eaf5ff2e250b00c50f380c5389a9c2d82e'      ,  )






import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_ta import TaTokenizer
else:
      __magic_name__  :  Dict					=       None


__magic_name__  :  Optional[Any]					=       logging.get_logger(__name__)

__magic_name__  :  Optional[Any]					=       {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

__magic_name__  :  Union[str, Any]					=       {
    """vocab_file""": {
        """t5-small""": """https://huggingface.co/t5-small/resolve/main/spiece.model""",
        """t5-base""": """https://huggingface.co/t5-base/resolve/main/spiece.model""",
        """t5-large""": """https://huggingface.co/t5-large/resolve/main/spiece.model""",
        """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/spiece.model""",
        """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """t5-small""": """https://huggingface.co/t5-small/resolve/main/tokenizer.json""",
        """t5-base""": """https://huggingface.co/t5-base/resolve/main/tokenizer.json""",
        """t5-large""": """https://huggingface.co/t5-large/resolve/main/tokenizer.json""",
        """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/tokenizer.json""",
        """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/tokenizer.json""",
    },
}


# TODO(PVP) - this should be removed in Transformers v5
__magic_name__  :  Tuple					=       {
    """t5-small""": 5_12,
    """t5-base""": 5_12,
    """t5-large""": 5_12,
    """t5-3b""": 5_12,
    """t5-11b""": 5_12,
}





class     SCREAMING_SNAKE_CASE__		(_a			):
     lowercase_ :      Dict				= VOCAB_FILES_NAMES
     lowercase_ :      Any				= PRETRAINED_VOCAB_FILES_MAP
     lowercase_ :      Tuple				= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase_ :      Tuple				= ["input_ids", "attention_mask"]
     lowercase_ :      Any				= TaTokenizer

     lowercase_ :      List[int]				= []
     def __init__(						self	:		Tuple       ,						__lowerCamelCase	:		Tuple=None       ,						__lowerCamelCase	:		str=None       ,						__lowerCamelCase	:		Optional[int]="</s>"       ,						__lowerCamelCase	:		Optional[Any]="<unk>"       ,						__lowerCamelCase	:		int="<pad>"       ,						__lowerCamelCase	:		int=1_00       ,						__lowerCamelCase	:		List[str]=None       ,						**__lowerCamelCase	:		Tuple       ,						):



       """simple docstring"""
       # Add extra_ids to the special token list
       if extra_ids > 0 and additional_special_tokens is None:
         lowerCAmelCase__										=      [F"""<extra_id_{i}>""" for i in range(__lowerCamelCase						)]
       elif extra_ids > 0 and additional_special_tokens is not None:
         # Check that we have the right number of extra special tokens
         lowerCAmelCase__										=      len(set(filter(lambda __lowerCamelCase						: bool('''extra_id_''' in str(__lowerCamelCase						)						)       ,						__lowerCamelCase						)						)						)
         if extra_tokens != extra_ids:
           raise ValueError(
               F"""Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"""
               ''' provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids'''
               ''' tokens'''						)

       super().__init__(
           __lowerCamelCase       ,						tokenizer_file=__lowerCamelCase       ,						eos_token=__lowerCamelCase       ,						unk_token=__lowerCamelCase       ,						pad_token=__lowerCamelCase       ,						extra_ids=__lowerCamelCase       ,						additional_special_tokens=__lowerCamelCase       ,						**__lowerCamelCase       ,						)

       lowerCAmelCase__										=      vocab_file
       lowerCAmelCase__										=      False if not self.vocab_file else True
       lowerCAmelCase__										=      extra_ids
     @staticmethod
     def        A__      (						__lowerCamelCase	:		Dict       ,						__lowerCamelCase	:		List[str]       ,						__lowerCamelCase	:		Any						):



       """simple docstring"""
       if pretrained_model_name_or_path in TaTokenizerFast.max_model_input_sizes:
         lowerCAmelCase__										=      TaTokenizerFast.max_model_input_sizes[pretrained_model_name_or_path]
         if init_max_model_length is not None and init_max_model_length != max_model_length:
           return init_max_model_length
         elif init_max_model_length is None:
           warnings.warn(
               '''This tokenizer was incorrectly instantiated with a model max length of'''
               F""" {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this"""
               ''' behavior is kept to avoid breaking backwards compatibility when padding/encoding with'''
               ''' `truncation is True`.\n- Be aware that you SHOULD NOT rely on'''
               F""" {pretrained_model_name_or_path} automatically truncating your input to"""
               F""" {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences"""
               F""" longer than {deprecated_max_model_length} you can either instantiate this tokenizer with"""
               ''' `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please'''
               ''' instantiate this tokenizer with `model_max_length` set to your preferred value.'''       ,						__lowerCamelCase       ,						)

       return max_model_length
     def        A__      (						self	:		int       ,						__lowerCamelCase	:		str       ,						__lowerCamelCase	:		Optional[str] = None						):



       """simple docstring"""
       if not self.can_save_slow_tokenizer:
         raise ValueError(
             '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
             '''tokenizer.'''						)

       if not os.path.isdir(__lowerCamelCase						):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
         return
       lowerCAmelCase__										=      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						)
         logger.info(F"""Copy vocab file to {out_vocab_file}"""						)

       return (out_vocab_file,)
     def        A__      (						self	:		Optional[Any]       ,						__lowerCamelCase	:		List[int]       ,						__lowerCamelCase	:		Optional[List[int]] = None						):



       """simple docstring"""
       lowerCAmelCase__										=      token_ids_a + [self.eos_token_id]
       if token_ids_a is None:
         return self.prefix_tokens + token_ids_a
       else:
         lowerCAmelCase__										=      token_ids_a + [self.eos_token_id]
         return self.prefix_tokens + token_ids_a + token_ids_a
     def        A__      (						self	:		int       ,						__lowerCamelCase	:		List[int]       ,						__lowerCamelCase	:		Optional[List[int]] = None						):



       """simple docstring"""
       lowerCAmelCase__										=      [self.eos_token_id]

       if token_ids_a is None:
         return len(token_ids_a + eos						) * [0]
       return len(token_ids_a + eos + token_ids_a + eos						) * [0]
     def        A__      (						self	:		int						):



       """simple docstring"""
       return list(
           set(filter(lambda __lowerCamelCase						: bool(re.search(r'''<extra_id_\d+>'''       ,						__lowerCamelCase						)						) is not None       ,						self.additional_special_tokens						)						)						)



     def        A__      (						self	:		Dict						):



       """simple docstring"""
       return [self.convert_tokens_to_ids(__lowerCamelCase						) for token in self.get_sentinel_tokens()]

