



'''simple docstring'''





from typing import Dict, List, Optional

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


lowercase_		       =  logging.get_logger(__name__)


lowercase_		       =  {
    "nielsr/canine-s": 2_048,
}

# Unicode defines 1,114,112 total “codepoints”
lowercase_		       =  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
lowercase_		       =  0

lowercase_		       =  0XE_0_0_0
lowercase_		       =  0XE_0_0_1
lowercase_		       =  0XE_0_0_2
lowercase_		       =  0XE_0_0_3
lowercase_		       =  0XE_0_0_4

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






class __A			(  A						):



 '''simple docstring'''







 __lowerCamelCase    :       Union[str, Any]          =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



 def __init__(self ,   A=chr(A       ) ,   A=chr(A       ) ,   A=chr(A       ) ,   A=chr(A       ) ,   A=chr(A       ) ,   A=chr(A       ) ,   A=False ,   A=2_048 ,   **A ,   )    ->     Optional[int]:


      """simple docstring"""



      _a      =  AddedToken(A ,   lstrip=A ,   rstrip=A       ) if isinstance(A ,   A       ) else bos_token
      _a      =  AddedToken(A ,   lstrip=A ,   rstrip=A       ) if isinstance(A ,   A       ) else eos_token
      _a      =  AddedToken(A ,   lstrip=A ,   rstrip=A       ) if isinstance(A ,   A       ) else sep_token
      _a      =  AddedToken(A ,   lstrip=A ,   rstrip=A       ) if isinstance(A ,   A       ) else cls_token
      _a      =  AddedToken(A ,   lstrip=A ,   rstrip=A       ) if isinstance(A ,   A       ) else pad_token

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

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

      # Creates a mapping for looking up the IDs of special symbols.
      _a      =  {}
      for codepoint, name in SPECIAL_CODEPOINTS.items():
           _a      =  codepoint

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

      _a      =  UNICODE_VOCAB_SIZE
      _a      =  len(self._special_codepoints       )



 @property
 def 					a__  (self       )    ->     int:


      """simple docstring"""



      return self._unicode_vocab_size



 def 					a__  (self ,   A       )    ->     List[str]:


      """simple docstring"""



      return list(A       )



 def 					a__  (self ,   A       )    ->     int:


      """simple docstring"""



      try:
           return ord(A       )
      except TypeError:
           raise ValueError(f'''invalid token: \'{token}\''''       )



 def 					a__  (self ,   A       )    ->     str:


      """simple docstring"""



      try:
           if index in SPECIAL_CODEPOINTS:
                return SPECIAL_CODEPOINTS[index]
           return chr(A       )
      except TypeError:
           raise ValueError(f'''invalid id: {index}'''       )



 def 					a__  (self ,   A       )    ->     int:


      """simple docstring"""



      return "".join(A       )



 def 					a__  (self ,   A ,   A = None       )    ->     List[int]:


      """simple docstring"""



      _a      =  [self.sep_token_id]
      _a      =  [self.cls_token_id]

      _a      =  cls + token_ids_a + sep
      if token_ids_a is not None:
           result += token_ids_a + sep
      return result



 def 					a__  (self ,   A ,   A = None ,   A = False       )    ->     List[int]:


      """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       )

      _a      =  [1] + ([0] * len(A       )) + [1]
      if token_ids_a is not None:
           result += ([0] * len(A       )) + [1]
      return result



 def 					a__  (self ,   A ,   A = None       )    ->     List[int]:


      """simple docstring"""



      _a      =  [self.sep_token_id]
      _a      =  [self.cls_token_id]

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



 def 					a__  (self ,   A ,   A = None       )    ->     List[str]:


      """simple docstring"""



      return ()








'''simple docstring'''





from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_		       =  {"configuration_mmbt": ["MMBTConfig"]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_		       =  ["MMBTForClassification", "MMBTModel", "ModalEmbeddings"]


if TYPE_CHECKING:
  from .configuration_mmbt import MMBTConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
  import sys

  lowercase_		       =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



