

'''simple docstring'''






import os
from typing import List, Optional, Union

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


lowerCAmelCase__											=	logging.get_logger(__name__)

lowerCAmelCase__											=	{'''vocab_file''': '''vocab.txt'''}

lowerCAmelCase__											=	{
    '''vocab_file''': {
        '''facebook/esm2_t6_8M_UR50D''': '''https://huggingface.co/facebook/esm2_t6_8M_UR50D/resolve/main/vocab.txt''',
        '''facebook/esm2_t12_35M_UR50D''': '''https://huggingface.co/facebook/esm2_t12_35M_UR50D/resolve/main/vocab.txt''',
    },
}

lowerCAmelCase__											=	{
    '''facebook/esm2_t6_8M_UR50D''': 1024,
    '''facebook/esm2_t12_35M_UR50D''': 1024,
}


def 		_A     (    A__      ):






 """simple docstring"""



 with open(A__     ,				'''r'''      ) as f:
  __lowercase							  = f.read().splitlines()
  return [l.strip() for l in lines]






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  Optional[int]							=			VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE    :  Optional[Any]							=			PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE    :  Optional[Any]							=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE    :  Any							=			['input_ids', 'attention_mask']






  def __init__(      self   :     Dict					,lowercase__   :     Optional[int]					,lowercase__   :     str="<unk>"					,lowercase__   :     Dict="<cls>"					,lowercase__   :     List[Any]="<pad>"					,lowercase__   :     Optional[int]="<mask>"					,lowercase__   :     str="<eos>"					,**lowercase__   :     Union[str, Any]					,):
   super().__init__(**lowercase__			)
   __lowercase							  = load_vocab_file(lowercase__			)
   __lowercase							  = dict(enumerate(self.all_tokens			)			)
   __lowercase							  = {tok: ind for ind, tok in enumerate(self.all_tokens			)}
   __lowercase							  = unk_token
   __lowercase							  = cls_token
   __lowercase							  = pad_token
   __lowercase							  = mask_token
   __lowercase							  = eos_token
   __lowercase							  = self.all_tokens
   self._create_trie(self.unique_no_split_tokens			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     int					,lowercase__   :     int			):
   return self._id_to_token.get(lowercase__					,self.unk_token			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Any					,lowercase__   :     str			):
   return self._token_to_id.get(lowercase__					,self._token_to_id.get(self.unk_token			)			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple					,lowercase__   :     Optional[int]					,**lowercase__   :     List[str]			):
   return text.split()






  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple					,lowercase__   :     Optional[Any]=False			):
   return len(self._id_to_token			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]			):
   return {token: i for i, token in enumerate(self.all_tokens			)}






  def 					SCREAMING_SNAKE_CASE      (      self   :     int					,lowercase__   :     str			):
   return self._token_to_id.get(lowercase__					,self._token_to_id.get(self.unk_token			)			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple					,lowercase__   :     int			):
   return self._id_to_token.get(lowercase__					,self.unk_token			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,lowercase__   :     List[int]					,lowercase__   :     Optional[List[int]] = None			):
   __lowercase							  = [self.cls_token_id]
   __lowercase							  = [self.eos_token_id]  # No sep token in ESM vocabulary
   if token_ids_a is None:
    if self.eos_token_id is None:
     return cls + token_ids_a
    else:
     return cls + token_ids_a + sep
   elif self.eos_token_id is None:
    raise ValueError('''Cannot tokenize multiple sequences when EOS token is not set!'''			)
   return cls + token_ids_a + sep + token_ids_a + sep  # Multiple inputs always have an EOS token






  def 					SCREAMING_SNAKE_CASE      (      self   :     Any					,lowercase__   :     List					,lowercase__   :     Optional[List] = None					,lowercase__   :     bool = False			):
   if already_has_special_tokens:
    if token_ids_a is not None:
     raise ValueError(
         '''You should not supply a second sequence if the provided sequence of '''
         '''ids is already formatted with special tokens for the model.'''			)

    return [1 if token in self.all_special_ids else 0 for token in token_ids_a]
   __lowercase							  = [1] + ([0] * len(lowercase__			)) + [1]
   if token_ids_a is not None:
    mask += [0] * len(lowercase__			) + [1]
   return mask






  def 					SCREAMING_SNAKE_CASE      (      self   :     int					,lowercase__   :     Optional[int]					,lowercase__   :     Dict			):
   __lowercase							  = os.path.join(lowercase__					,(filename_prefix + '''-''' if filename_prefix else '''''') + '''vocab.txt'''			)
   with open(lowercase__					,'''w'''			) as f:
    f.write('''\n'''.join(self.all_tokens			)			)
   return (vocab_file,)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple			):
   return self.get_vocab_size(with_added_tokens=lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Dict					,lowercase__   :     Union[List[str], List[AddedToken]]					,lowercase__   :     bool = False			):
   return super()._add_tokens(lowercase__					,special_tokens=lowercase__			)




'''simple docstring'''






import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  Optional[Any]							=			['image_processor', 'tokenizer']
  SCREAMING_SNAKE_CASE    :  Union[str, Any]							=			'CLIPImageProcessor'
  SCREAMING_SNAKE_CASE    :  Union[str, Any]							=			('CLIPTokenizer', 'CLIPTokenizerFast')






  def __init__(      self   :     List[Any]					,lowercase__   :     Dict=None					,lowercase__   :     Union[str, Any]=None					,**lowercase__   :     Tuple			):
   __lowercase							  = None
   if "feature_extractor" in kwargs:
    warnings.warn(
        '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
        ''' instead.'''					,lowercase__					,)
    __lowercase							  = kwargs.pop('''feature_extractor'''			)

   __lowercase							  = image_processor if image_processor is not None else feature_extractor
   if image_processor is None:
    raise ValueError('''You need to specify an `image_processor`.'''			)
   if tokenizer is None:
    raise ValueError('''You need to specify a `tokenizer`.'''			)

   super().__init__(lowercase__					,lowercase__			)






  def __call__(      self   :     List[Any]					,lowercase__   :     str=None					,lowercase__   :     List[Any]=None					,lowercase__   :     Optional[Any]=None					,**lowercase__   :     int			):

   if text is None and images is None:
    raise ValueError('''You have to specify either text or images. Both cannot be none.'''			)

   if text is not None:
    __lowercase							  = self.tokenizer(lowercase__					,return_tensors=lowercase__					,**lowercase__			)

   if images is not None:
    __lowercase							  = self.image_processor(lowercase__					,return_tensors=lowercase__					,**lowercase__			)

   if text is not None and images is not None:
    __lowercase							  = image_features.pixel_values
    return encoding
   elif text is not None:
    return encoding
   else:
    return BatchEncoding(data=dict(**lowercase__			)					,tensor_type=lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,*lowercase__   :     List[str]					,**lowercase__   :     int			):
   return self.tokenizer.batch_decode(*lowercase__					,**lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     List[Any]					,*lowercase__   :     Optional[int]					,**lowercase__   :     Union[str, Any]			):
   return self.tokenizer.decode(*lowercase__					,**lowercase__			)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[Any]			):
   __lowercase							  = self.tokenizer.model_input_names
   __lowercase							  = self.image_processor.model_input_names
   return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     List[str]			):
   warnings.warn(
       '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''					,lowercase__					,)
   return self.image_processor_class






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]			):
   warnings.warn(
       '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''					,lowercase__					,)
   return self.image_processor

