



from typing import Dict, List, Optional

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


__UpperCAmelCase	       =	logging.get_logger(__name__)


__UpperCAmelCase	       =	{
    '''nielsr/canine-s''': 2_048,
}

# Unicode defines 1,114,112 total “codepoints”
__UpperCAmelCase	       =	1_114_112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
__UpperCAmelCase	       =	0

__UpperCAmelCase	       =	0XE_000
__UpperCAmelCase	       =	0XE_001
__UpperCAmelCase	       =	0XE_002
__UpperCAmelCase	       =	0XE_003
__UpperCAmelCase	       =	0XE_004

# Maps special codepoints to human-readable names.
__UpperCAmelCase	       =	{
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: "[CLS]",
    SEP: "[SEP]",
    BOS: "[BOS]",
    MASK: "[MASK]",
    PAD: "[PAD]",
    RESERVED: "[RESERVED]",
}

# Maps special codepoint human-readable names to their codepoint values.
__UpperCAmelCase	       =	{name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}



class     lowerCAmelCase_		(  a__							):
       UpperCAmelCase__    : str       					=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       def __init__(      self,      SCREAMING_SNAKE_CASE_=chr(SCREAMING_SNAKE_CASE_	),      SCREAMING_SNAKE_CASE_=chr(SCREAMING_SNAKE_CASE_	),      SCREAMING_SNAKE_CASE_=chr(SCREAMING_SNAKE_CASE_	),      SCREAMING_SNAKE_CASE_=chr(SCREAMING_SNAKE_CASE_	),      SCREAMING_SNAKE_CASE_=chr(SCREAMING_SNAKE_CASE_	),      SCREAMING_SNAKE_CASE_=chr(SCREAMING_SNAKE_CASE_	),      SCREAMING_SNAKE_CASE_=False,      SCREAMING_SNAKE_CASE_=2048,      **SCREAMING_SNAKE_CASE_,      )					->		List[Any]:
          UpperCamelCase   :  Union[str, Any]						     =     AddedToken(SCREAMING_SNAKE_CASE_,      lstrip=SCREAMING_SNAKE_CASE_,      rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_	) else bos_token
          UpperCamelCase   :  List[str]						     =     AddedToken(SCREAMING_SNAKE_CASE_,      lstrip=SCREAMING_SNAKE_CASE_,      rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_	) else eos_token
          UpperCamelCase   :  str						     =     AddedToken(SCREAMING_SNAKE_CASE_,      lstrip=SCREAMING_SNAKE_CASE_,      rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_	) else sep_token
          UpperCamelCase   :  str						     =     AddedToken(SCREAMING_SNAKE_CASE_,      lstrip=SCREAMING_SNAKE_CASE_,      rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_	) else cls_token
          UpperCamelCase   :  Tuple						     =     AddedToken(SCREAMING_SNAKE_CASE_,      lstrip=SCREAMING_SNAKE_CASE_,      rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_	) else pad_token

          # Mask token behave like a normal word, i.e. include the space before it
          UpperCamelCase   :  Tuple						     =     AddedToken(SCREAMING_SNAKE_CASE_,      lstrip=SCREAMING_SNAKE_CASE_,      rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_	) else mask_token

          super().__init__(
              bos_token=SCREAMING_SNAKE_CASE_,      eos_token=SCREAMING_SNAKE_CASE_,      sep_token=SCREAMING_SNAKE_CASE_,      cls_token=SCREAMING_SNAKE_CASE_,      pad_token=SCREAMING_SNAKE_CASE_,      mask_token=SCREAMING_SNAKE_CASE_,      add_prefix_space=SCREAMING_SNAKE_CASE_,      model_max_length=SCREAMING_SNAKE_CASE_,      **SCREAMING_SNAKE_CASE_,      )

          # Creates a mapping for looking up the IDs of special symbols.
          UpperCamelCase   :  Dict[str, int]						     =     {}
          for codepoint, name in SPECIAL_CODEPOINTS.items():
             UpperCamelCase   :  Union[str, Any]						     =     codepoint

          # Creates a mapping for looking up the string forms of special symbol IDs.
          UpperCamelCase   :  Dict[int, str]						     =     {
              codepoint: name for name, codepoint in self._special_codepoints.items()
          }

          UpperCamelCase   :  Dict						     =     UNICODE_VOCAB_SIZE
          UpperCamelCase   :  Union[str, Any]						     =     len(self._special_codepoints	)
       @property
       def  snake_case_	(      self	)					->		int:
          return self._unicode_vocab_size
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_	)					->		List[str]:
          return list(SCREAMING_SNAKE_CASE_	)
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_	)					->		int:
          try:
             return ord(SCREAMING_SNAKE_CASE_	)
          except TypeError:
             raise ValueError(F"""invalid token: '{token}'"""	)
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_	)					->		str:
          try:
             if index in SPECIAL_CODEPOINTS:
                return SPECIAL_CODEPOINTS[index]
             return chr(SCREAMING_SNAKE_CASE_	)
          except TypeError:
             raise ValueError(F"""invalid id: {index}"""	)
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_	)					->		List[str]:
          return "".join(SCREAMING_SNAKE_CASE_	)
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_ = None	)					->		List[int]:
          UpperCamelCase   :  Union[str, Any]						     =     [self.sep_token_id]
          UpperCamelCase   :  Any						     =     [self.cls_token_id]

          UpperCamelCase   :  Optional[int]						     =     cls + token_ids_a + sep
          if token_ids_a is not None:
             result += token_ids_a + sep
          return result
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_ = None,      SCREAMING_SNAKE_CASE_ = False	)					->		List[int]:
          if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=SCREAMING_SNAKE_CASE_,      token_ids_a=SCREAMING_SNAKE_CASE_,      already_has_special_tokens=SCREAMING_SNAKE_CASE_	)

          UpperCamelCase   :  Dict						     =     [1] + ([0] * len(SCREAMING_SNAKE_CASE_	)) + [1]
          if token_ids_a is not None:
             result += ([0] * len(SCREAMING_SNAKE_CASE_	)) + [1]
          return result
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_ = None	)					->		List[int]:
          UpperCamelCase   :  Any						     =     [self.sep_token_id]
          UpperCamelCase   :  List[Any]						     =     [self.cls_token_id]

          UpperCamelCase   :  Optional[int]						     =     len(cls + token_ids_a + sep	) * [0]
          if token_ids_a is not None:
             result += len(token_ids_a + sep	) * [1]
          return result






       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_ = None	)					->		Dict:
          return ()








import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch



class     lowerCAmelCase_		(  unittest.TestCase							):
       UpperCAmelCase__    : Union[str, Any]       					=  JukeboxTokenizer
       UpperCAmelCase__    : Optional[int]       					=  {
           "artist": "Zac Brown Band",
           "genres": "Country",
           "lyrics": "I met a traveller from an antique land,\n        Who said \"Two vast and trunkless legs of stone\n        Stand in the desert. . . . Near them, on the sand,\n        Half sunk a shattered visage lies, whose frown,\n        And wrinkled lip, and sneer of cold command,\n        Tell that its sculptor well those passions read\n        Which yet survive, stamped on these lifeless things,\n        The hand that mocked them, and the heart that fed;\n        And on the pedestal, these words appear:\n        My name is Ozymandias, King of Kings;\n        Look on my Works, ye Mighty, and despair!\n        Nothing beside remains. Round the decay\n        Of that colossal Wreck, boundless and bare\n        The lone and level sands stretch far away\n        ",
       }
       @require_torch
       def  snake_case_	(      self	)					->		Optional[Any]:
          import torch

          UpperCamelCase   :  Tuple						     =     JukeboxTokenizer.from_pretrained('openai/jukebox-1b-lyrics'	)
          UpperCamelCase   :  List[str]						     =     tokenizer(**self.metas	)['input_ids']
          # fmt: off
          UpperCamelCase   :  Dict						     =     [
              torch.tensor([[
                  0, 0, 0, 7169, 507, 9, 76, 39, 31, 46, 76, 27,
                  76, 46, 44, 27, 48, 31, 38, 38, 31, 44, 76, 32,
                  44, 41, 39, 76, 27, 40, 76, 27, 40, 46, 35, 43,
                  47, 31, 76, 38, 27, 40, 30, 64, 78, 76, 76, 76,
                  76, 76, 76, 76, 76, 23, 34, 41, 76, 45, 27, 35,
                  30, 76, 71, 20, 49, 41, 76, 48, 27, 45, 46, 76,
                  27, 40, 30, 76, 46, 44, 47, 40, 37, 38, 31, 45,
                  45, 76, 38, 31, 33, 45, 76, 41, 32, 76, 45, 46,
                  41, 40, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
                  19, 46, 27, 40, 30, 76, 35, 40, 76, 46, 34, 31,
                  76, 30, 31, 45, 31, 44, 46, 63, 76, 63, 76, 63,
                  76, 63, 76, 14, 31, 27, 44, 76, 46, 34, 31, 39,
                  64, 76, 41, 40, 76, 46, 34, 31, 76, 45, 27, 40,
                  30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76, 8,
                  27, 38, 32, 76, 45, 47, 40, 37, 76, 27, 76, 45,
                  34, 27, 46, 46, 31, 44, 31, 30, 76, 48, 35, 45,
                  27, 33, 31, 76, 38, 35, 31, 45, 64, 76, 49, 34,
                  41, 45, 31, 76, 32, 44, 41, 49, 40, 64, 78, 76,
                  76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76, 49,
                  44, 35, 40, 37, 38, 31, 30, 76, 38, 35, 42, 64,
                  76, 27, 40, 30, 76, 45, 40, 31, 31, 44, 76, 41,
                  32, 76, 29, 41, 38, 30, 76, 29, 41, 39, 39, 27,
                  40, 30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76,
                  20, 31, 38, 38, 76, 46, 34, 27, 46, 76, 35, 46,
                  45, 76, 45, 29, 47, 38, 42, 46, 41, 44, 76, 49,
                  31, 38, 38, 76, 46, 34, 41, 45, 31, 76, 42, 27,
                  45, 45, 35, 41, 40, 45, 76, 44, 31, 27, 30, 78,
                  76, 76, 76, 76, 76, 76, 76, 76, 23, 34, 35, 29,
                  34, 76, 51, 31, 46, 76, 45, 47, 44, 48, 35, 48,
                  31, 64, 76, 45, 46, 27, 39, 42, 31, 30, 76, 41,
                  40, 76, 46, 34, 31, 45, 31, 76, 38, 35, 32, 31,
                  38, 31, 45, 45, 76, 46, 34, 35, 40, 33, 45, 64,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 20, 34, 31,
                  76, 34, 27, 40, 30, 76, 46, 34, 27, 46, 76, 39,
                  41, 29, 37, 31, 30, 76, 46, 34, 31, 39, 64, 76,
                  27, 40, 30, 76, 46, 34, 31, 76, 34, 31, 27, 44,
                  46, 76, 46, 34, 27, 46, 76, 32, 31, 30, 66, 78,
                  76, 76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76,
                  41, 40, 76, 46, 34, 31, 76, 42, 31, 30, 31, 45,
                  46, 27, 38, 64, 76, 46, 34, 31, 45, 31, 76, 49,
                  41, 44, 30, 45, 76, 27, 42, 42, 31, 27, 44, 65,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 13, 51, 76,
                  40, 27, 39, 31, 76, 35, 45, 76, 15, 52, 51, 39,
                  27, 40, 30, 35, 27, 45, 64, 76, 11, 35, 40, 33,
                  76, 41, 32, 76, 11, 35, 40, 33, 45, 66, 78, 76,
                  76, 76, 76, 76, 76, 76, 76, 12, 41, 41, 37, 76,
                  41, 40, 76, 39, 51, 76, 23, 41, 44, 37, 45, 64,
                  76, 51, 31, 76, 13, 35, 33, 34, 46, 51, 64, 76,
                  27, 40, 30, 76, 30, 31, 45, 42, 27, 35, 44, 67,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 14, 41, 46,
                  34, 35, 40, 33, 76, 28, 31, 45, 35, 30, 31, 76,
                  44, 31, 39, 27, 35, 40, 45, 63, 76, 18, 41, 47,
                  40, 30, 76, 46, 34, 31, 76, 30, 31, 29, 27, 51,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 15, 32, 76,
                  46, 34, 27, 46, 76, 29, 41, 38, 41, 45, 45, 27,
                  38, 76, 23, 44, 31, 29, 37, 64, 76, 28, 41, 47,
                  40, 30, 38, 31, 45, 45, 76, 27, 40, 30, 76, 28,
                  27, 44, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
                  20, 34, 31, 76, 38, 41, 40, 31, 76, 27, 40, 30,
                  76, 38, 31, 48, 31, 38, 76, 45, 27, 40, 30, 45,
                  76, 45, 46, 44, 31, 46, 29, 34, 76, 32, 27, 44,
                  76, 27, 49, 27, 51, 78, 76, 76, 76, 76, 76, 76,
                  76, 76]]	),
              torch.tensor([[0, 0, 0, 1069, 11]]	),
              torch.tensor([[0, 0, 0, 1069, 11]]	),
          ]
          # fmt: on
          self.assertTrue(torch.allclose(tokens[0],      EXPECTED_OUTPUT[0]	)	)
          self.assertTrue(torch.allclose(tokens[1],      EXPECTED_OUTPUT[1]	)	)
          self.assertTrue(torch.allclose(tokens[2],      EXPECTED_OUTPUT[2]	)	)






       @require_torch
       def  snake_case_	(      self	)					->		Optional[Any]:
          import torch

          UpperCamelCase   :  str						     =     JukeboxTokenizer.from_pretrained('openai/jukebox-5b-lyrics'	)
          UpperCamelCase   :  Dict						     =     tokenizer(**self.metas	)['input_ids']
          # fmt: off
          UpperCamelCase   :  Optional[int]						     =     [
              torch.tensor([[
                  0, 0, 0, 1069, 11, -1, -1, -1, -1, 9, 77, 39,
                  31, 46, 77, 27, 77, 46, 44, 27, 48, 31, 38, 38,
                  31, 44, 77, 32, 44, 41, 39, 77, 27, 40, 77, 27,
                  40, 46, 35, 43, 47, 31, 77, 38, 27, 40, 30, 64,
                  79, 77, 77, 77, 77, 77, 77, 77, 77, 23, 34, 41,
                  77, 45, 27, 35, 30, 77, 72, 20, 49, 41, 77, 48,
                  27, 45, 46, 77, 27, 40, 30, 77, 46, 44, 47, 40,
                  37, 38, 31, 45, 45, 77, 38, 31, 33, 45, 77, 41,
                  32, 77, 45, 46, 41, 40, 31, 79, 77, 77, 77, 77,
                  77, 77, 77, 77, 19, 46, 27, 40, 30, 77, 35, 40,
                  77, 46, 34, 31, 77, 30, 31, 45, 31, 44, 46, 63,
                  77, 63, 77, 63, 77, 63, 77, 14, 31, 27, 44, 77,
                  46, 34, 31, 39, 64, 77, 41, 40, 77, 46, 34, 31,
                  77, 45, 27, 40, 30, 64, 79, 77, 77, 77, 77, 77,
                  77, 77, 77, 8, 27, 38, 32, 77, 45, 47, 40, 37,
                  77, 27, 77, 45, 34, 27, 46, 46, 31, 44, 31, 30,
                  77, 48, 35, 45, 27, 33, 31, 77, 38, 35, 31, 45,
                  64, 77, 49, 34, 41, 45, 31, 77, 32, 44, 41, 49,
                  40, 64, 79, 77, 77, 77, 77, 77, 77, 77, 77, 1,
                  40, 30, 77, 49, 44, 35, 40, 37, 38, 31, 30, 77,
                  38, 35, 42, 64, 77, 27, 40, 30, 77, 45, 40, 31,
                  31, 44, 77, 41, 32, 77, 29, 41, 38, 30, 77, 29,
                  41, 39, 39, 27, 40, 30, 64, 79, 77, 77, 77, 77,
                  77, 77, 77, 77, 20, 31, 38, 38, 77, 46, 34, 27,
                  46, 77, 35, 46, 45, 77, 45, 29, 47, 38, 42, 46,
                  41, 44, 77, 49, 31, 38, 38, 77, 46, 34, 41, 45,
                  31, 77, 42, 27, 45, 45, 35, 41, 40, 45, 77, 44,
                  31, 27, 30, 79, 77, 77, 77, 77, 77, 77, 77, 77,
                  23, 34, 35, 29, 34, 77, 51, 31, 46, 77, 45, 47,
                  44, 48, 35, 48, 31, 64, 77, 45, 46, 27, 39, 42,
                  31, 30, 77, 41, 40, 77, 46, 34, 31, 45, 31, 77,
                  38, 35, 32, 31, 38, 31, 45, 45, 77, 46, 34, 35,
                  40, 33, 45, 64, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 20, 34, 31, 77, 34, 27, 40, 30, 77, 46, 34,
                  27, 46, 77, 39, 41, 29, 37, 31, 30, 77, 46, 34,
                  31, 39, 64, 77, 27, 40, 30, 77, 46, 34, 31, 77,
                  34, 31, 27, 44, 46, 77, 46, 34, 27, 46, 77, 32,
                  31, 30, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77,
                  1, 40, 30, 77, 41, 40, 77, 46, 34, 31, 77, 42,
                  31, 30, 31, 45, 46, 27, 38, 64, 77, 46, 34, 31,
                  45, 31, 77, 49, 41, 44, 30, 45, 77, 27, 42, 42,
                  31, 27, 44, 65, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 13, 51, 77, 40, 27, 39, 31, 77, 35, 45, 77,
                  15, 52, 51, 39, 27, 40, 30, 35, 27, 45, 64, 77,
                  11, 35, 40, 33, 77, 41, 32, 77, 11, 35, 40, 33,
                  45, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77, 12,
                  41, 41, 37, 77, 41, 40, 77, 39, 51, 77, 23, 41,
                  44, 37, 45, 64, 77, 51, 31, 77, 13, 35, 33, 34,
                  46, 51, 64, 77, 27, 40, 30, 77, 30, 31, 45, 42,
                  27, 35, 44, 67, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 14, 41, 46, 34, 35, 40, 33, 77, 28, 31, 45,
                  35, 30, 31, 77, 44, 31, 39, 27, 35, 40, 45, 63,
                  77, 18, 41, 47, 40, 30, 77, 46, 34, 31, 77, 30,
                  31, 29, 27, 51, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 15, 32, 77, 46, 34, 27, 46, 77, 29, 41, 38,
                  41, 45, 45, 27, 38, 77, 23, 44, 31, 29, 37, 64,
                  77, 28, 41, 47, 40, 30, 38, 31, 45, 45, 77, 27,
                  40, 30, 77, 28, 27, 44, 31, 79, 77, 77, 77, 77,
                  77, 77, 77, 77, 20, 34, 31, 77, 38, 41, 40, 31,
                  77, 27, 40, 30, 77, 38, 31, 48, 31, 38, 77, 45,
                  27, 40, 30, 45, 77, 45, 46, 44, 31, 46, 29, 34,
                  77, 32, 27, 44, 77, 27, 49, 27, 51, 79, 77, 77,
                  77, 77, 77, 77, 77, 77]]	),
              torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]	),
              torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]	),
          ]
          # fmt: on
          self.assertTrue(torch.allclose(tokens[0],      EXPECTED_OUTPUT[0]	)	)
          self.assertTrue(torch.allclose(tokens[1],      EXPECTED_OUTPUT[1]	)	)
          self.assertTrue(torch.allclose(tokens[2],      EXPECTED_OUTPUT[2]	)	)



