

'''simple docstring'''






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






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  List[str]							=			['image_processor', 'tokenizer']
  SCREAMING_SNAKE_CASE    :  List[Any]							=			'AutoImageProcessor'
  SCREAMING_SNAKE_CASE    :  Union[str, Any]							=			'AutoTokenizer'






  def __init__(      self   :     Dict					,lowercase__   :     int					,lowercase__   :     List[Any]			):
   super().__init__(lowercase__					,lowercase__			)
   __lowercase							  = self.image_processor






  def __call__(      self   :     int					,lowercase__   :     Dict=None					,lowercase__   :     int=None					,lowercase__   :     str=None					,**lowercase__   :     str			):

   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   :     str					,*lowercase__   :     Union[str, Any]					,**lowercase__   :     Optional[Any]			):
   return self.tokenizer.batch_decode(*lowercase__					,**lowercase__			)






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






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     List[str]			):
   return ["input_ids", "attention_mask", "pixel_values"]





'''simple docstring'''


from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_		:   Dict							   =		logging.get_logger(__name__)

UpperCAmelCase_		:   Optional[int]							   =		{
    'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
    # See all CANINE models at https://huggingface.co/models?filter=canine
}





class     lowercase__  (						_snake_case					):





							'''simple docstring'''


							A_							:      Optional[int]      	=  """canine"""






							def __init__(    self    ,					__snake_case=768    ,					__snake_case=12    ,					__snake_case=12    ,					__snake_case=3072    ,					__snake_case="gelu"    ,					__snake_case=0.1    ,					__snake_case=0.1    ,					__snake_case=1_6384    ,					__snake_case=16    ,					__snake_case=0.02    ,					__snake_case=1e-12    ,					__snake_case=0    ,					__snake_case=0XE000    ,					__snake_case=0XE001    ,					__snake_case=4    ,					__snake_case=4    ,					__snake_case=8    ,					__snake_case=1_6384    ,					__snake_case=128    ,					**__snake_case    ,					):
											super().__init__(pad_token_id=__snake_case    ,					bos_token_id=__snake_case    ,					eos_token_id=__snake_case    ,					**__snake_case  )

											_SCREAMING_SNAKE_CASE :       str     		=      max_position_embeddings
											_SCREAMING_SNAKE_CASE :       Any     		=      hidden_size
											_SCREAMING_SNAKE_CASE :       Dict     		=      num_hidden_layers
											_SCREAMING_SNAKE_CASE :       Tuple     		=      num_attention_heads
											_SCREAMING_SNAKE_CASE :       List[str]     		=      intermediate_size
											_SCREAMING_SNAKE_CASE :       Tuple     		=      hidden_act
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      hidden_dropout_prob
											_SCREAMING_SNAKE_CASE :       str     		=      attention_probs_dropout_prob
											_SCREAMING_SNAKE_CASE :       Dict     		=      initializer_range
											_SCREAMING_SNAKE_CASE :       Optional[int]     		=      type_vocab_size
											_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      layer_norm_eps

											# Character config:
											_SCREAMING_SNAKE_CASE :       Any     		=      downsampling_rate
											_SCREAMING_SNAKE_CASE :       List[str]     		=      upsampling_kernel_size
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      num_hash_functions
											_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      num_hash_buckets
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      local_transformer_stride




