

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







class 		__magic_name__     (				lowerCamelCase__				):

   '''simple docstring'''




   lowerCamelCase__					:      List[Any]        =  ['image_processor', 'tokenizer']
   lowerCamelCase__					:      Dict        =  'EfficientNetImageProcessor'
   lowerCamelCase__					:      Optional[int]        =  ('BertTokenizer', 'BertTokenizerFast')



   def __init__(							self,       lowercase_,       lowercase_			)				->       Optional[int]:






     """simple docstring"""






     super().__init__(lowercase_,       lowercase_			)



   def __call__(							self,       lowercase_=None,       lowercase_=None,       lowercase_="max_length",       lowercase_=64,       lowercase_=None,       **lowercase_			)				->       int:






     """simple docstring"""






     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:
       a__    =self.tokenizer(
           lowercase_,       padding=lowercase_,       max_length=lowercase_,       return_tensors=lowercase_,       **lowercase_			)

     if images is not None:
       a__    =self.image_processor(lowercase_,       return_tensors=lowercase_,       **lowercase_			)

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



   def 					_UpperCAmelCase					(							self,       *lowercase_,       **lowercase_			)				->       int:






     """simple docstring"""






     return self.tokenizer.batch_decode(*lowercase_,       **lowercase_			)



   def 					_UpperCAmelCase					(							self,       *lowercase_,       **lowercase_			)				->       str:






     """simple docstring"""






     return self.tokenizer.decode(*lowercase_,       **lowercase_			)



   @property
   def 					_UpperCAmelCase					(							self			)				->       Tuple:






     """simple docstring"""






     a__    =self.tokenizer.model_input_names
     a__    =self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)



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


lowerCamelCase 	=   logging.get_logger(__name__)

lowerCamelCase 	=   {
    '''uw-madison/yoso-4096''': '''https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json''',
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}







class 		__magic_name__     (				lowerCamelCase__				):

   '''simple docstring'''




   lowerCamelCase__					:      Tuple        =  'yoso'



   def __init__(							self,       lowercase_=50265,       lowercase_=768,       lowercase_=12,       lowercase_=12,       lowercase_=3072,       lowercase_="gelu",       lowercase_=0.1,       lowercase_=0.1,       lowercase_=4096,       lowercase_=1,       lowercase_=0.02,       lowercase_=1E-12,       lowercase_="absolute",       lowercase_=True,       lowercase_=9,       lowercase_=64,       lowercase_=None,       lowercase_=True,       lowercase_=True,       lowercase_=1,       lowercase_=0,       lowercase_=2,       **lowercase_,       )				->       List[str]:






     """simple docstring"""






     super().__init__(pad_token_id=lowercase_,       bos_token_id=lowercase_,       eos_token_id=lowercase_,       **lowercase_			)

     a__    =vocab_size
     a__    =max_position_embeddings
     a__    =hidden_size
     a__    =num_hidden_layers
     a__    =num_attention_heads
     a__    =intermediate_size
     a__    =hidden_act
     a__    =hidden_dropout_prob
     a__    =attention_probs_dropout_prob
     a__    =initializer_range
     a__    =type_vocab_size
     a__    =layer_norm_eps
     a__    =position_embedding_type
     a__    =use_expectation
     a__    =hash_code_len
     a__    =num_hash
     a__    =conv_window
     a__    =use_fast_hash
     a__    =lsh_backward
