





"""simple docstring"""





import copy
import random

from transformers import CLIPTokenizer






class    _lowerCAmelCase  (	a			):
       """simple docstring"""




       def __init__(       self       ,					*__UpperCAmelCase       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         super().__init__(*__UpperCAmelCase       ,					**__UpperCAmelCase )
         lowerCAmelCase__     :List[Any]											=				{}






       def 	snake_case		(       self       ,					__UpperCAmelCase       ,					*__UpperCAmelCase       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[int]											=				super().add_tokens(__UpperCAmelCase       ,					*__UpperCAmelCase       ,					**__UpperCAmelCase )
         if num_added_tokens == 0:
           raise ValueError(
               F"The tokenizer already contains the token {placeholder_token}. Please pass a different"
               ' `placeholder_token` that is not already in the tokenizer.' )






       def 	snake_case		(       self       ,					__UpperCAmelCase       ,					*__UpperCAmelCase       ,					__UpperCAmelCase=1       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :int											=				[]
         if num_vec_per_token == 1:
           self.try_adding_tokens(__UpperCAmelCase       ,					*__UpperCAmelCase       ,					**__UpperCAmelCase )
           output.append(__UpperCAmelCase )
         else:
           lowerCAmelCase__     :Dict											=				[]
           for i in range(__UpperCAmelCase ):
             lowerCAmelCase__     :Tuple											=				placeholder_token + F"_{i}"
             self.try_adding_tokens(__UpperCAmelCase       ,					*__UpperCAmelCase       ,					**__UpperCAmelCase )
             output.append(__UpperCAmelCase )
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
         for token in self.token_map:
           if token in placeholder_token:
             raise ValueError(
                 F"The tokenizer already has placeholder token {token} that can get confused with"
                 F" {placeholder_token}keep placeholder tokens independent" )
         lowerCAmelCase__     :Tuple											=				output






       def 	snake_case		(       self       ,					__UpperCAmelCase       ,					__UpperCAmelCase=False       ,					__UpperCAmelCase=1.0 ):



         '''simple docstring'''

         if isinstance(__UpperCAmelCase       ,					__UpperCAmelCase ):
           lowerCAmelCase__     :Any											=				[]
           for i in range(len(__UpperCAmelCase ) ):
             output.append(self.replace_placeholder_tokens_in_text(text[i]       ,					vector_shuffle=__UpperCAmelCase ) )
           return output
         for placeholder_token in self.token_map:
           if placeholder_token in text:
             lowerCAmelCase__     :List[str]											=				self.token_map[placeholder_token]
             lowerCAmelCase__     :List[Any]											=				tokens[: 1 + int(len(__UpperCAmelCase ) * prop_tokens_to_load )]
             if vector_shuffle:
               lowerCAmelCase__     :Optional[int]											=				copy.copy(__UpperCAmelCase )
               random.shuffle(__UpperCAmelCase )
             lowerCAmelCase__     :str											=				text.replace(__UpperCAmelCase       ,					' '.join(__UpperCAmelCase ) )
         return text






       def __call__(       self       ,					__UpperCAmelCase       ,					*__UpperCAmelCase       ,					__UpperCAmelCase=False       ,					__UpperCAmelCase=1.0       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return super().__call__(
             self.replace_placeholder_tokens_in_text(
                 __UpperCAmelCase       ,					vector_shuffle=__UpperCAmelCase       ,					prop_tokens_to_load=__UpperCAmelCase )       ,					*__UpperCAmelCase       ,					**__UpperCAmelCase       ,					)






       def 	snake_case		(       self       ,					__UpperCAmelCase       ,					*__UpperCAmelCase       ,					__UpperCAmelCase=False       ,					__UpperCAmelCase=1.0       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return super().encode(
             self.replace_placeholder_tokens_in_text(
                 __UpperCAmelCase       ,					vector_shuffle=__UpperCAmelCase       ,					prop_tokens_to_load=__UpperCAmelCase )       ,					*__UpperCAmelCase       ,					**__UpperCAmelCase       ,					)







"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A											=						{"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A											=						[
      """SEW_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """SEWForCTC""",
      """SEWForSequenceClassification""",
      """SEWModel""",
      """SEWPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_sew import (
        SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
        SEWForCTC,
        SEWForSequenceClassification,
        SEWModel,
        SEWPreTrainedModel,
    )


else:
  import sys

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