




'''simple docstring'''



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


lowerCamelCase_			=						logging.get_logger(__name__)

lowerCamelCase_			=						{
    'microsoft/trocr-base-handwritten': (
        'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}







class 		lowercase_   (			A       ):


   """simple docstring"""

   lowerCamelCase_      =						'''trocr'''
   lowerCamelCase_      =						['''past_key_values''']
   lowerCamelCase_      =						{
       '''num_attention_heads''': '''decoder_attention_heads''',
       '''hidden_size''': '''d_model''',
       '''num_hidden_layers''': '''decoder_layers''',
   }



   def __init__(   self :     Optional[Any]  ,				__lowerCamelCase :     List[Any]=5_0_2_6_5  ,				__lowerCamelCase :     Optional[int]=1_0_2_4  ,				__lowerCamelCase :     Any=1_2  ,				__lowerCamelCase :     Tuple=1_6  ,				__lowerCamelCase :     str=4_0_9_6  ,				__lowerCamelCase :     Any="gelu"  ,				__lowerCamelCase :     int=5_1_2  ,				__lowerCamelCase :     Optional[int]=0.1  ,				__lowerCamelCase :     List[Any]=0.0  ,				__lowerCamelCase :     int=0.0  ,				__lowerCamelCase :     Optional[Any]=2  ,				__lowerCamelCase :     List[Any]=0.0_2  ,				__lowerCamelCase :     str=0.0  ,				__lowerCamelCase :     List[str]=True  ,				__lowerCamelCase :     Optional[int]=False  ,				__lowerCamelCase :     Dict=True  ,				__lowerCamelCase :     Any=True  ,				__lowerCamelCase :     Union[str, Any]=1  ,				__lowerCamelCase :     List[str]=0  ,				__lowerCamelCase :     Tuple=2  ,				**__lowerCamelCase :     Any  ,				):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				vocab_size
      _SCREAMING_SNAKE_CASE	=				d_model
      _SCREAMING_SNAKE_CASE	=				decoder_layers
      _SCREAMING_SNAKE_CASE	=				decoder_attention_heads
      _SCREAMING_SNAKE_CASE	=				decoder_ffn_dim
      _SCREAMING_SNAKE_CASE	=				activation_function
      _SCREAMING_SNAKE_CASE	=				max_position_embeddings
      _SCREAMING_SNAKE_CASE	=				dropout
      _SCREAMING_SNAKE_CASE	=				attention_dropout
      _SCREAMING_SNAKE_CASE	=				activation_dropout
      _SCREAMING_SNAKE_CASE	=				init_std
      _SCREAMING_SNAKE_CASE	=				decoder_layerdrop
      _SCREAMING_SNAKE_CASE	=				use_cache
      _SCREAMING_SNAKE_CASE	=				scale_embedding
      _SCREAMING_SNAKE_CASE	=				use_learned_position_embeddings
      _SCREAMING_SNAKE_CASE	=				layernorm_embedding

      super().__init__(
          pad_token_id=__lowerCamelCase  ,				bos_token_id=__lowerCamelCase  ,				eos_token_id=__lowerCamelCase  ,				decoder_start_token_id=__lowerCamelCase  ,				**__lowerCamelCase  ,				)







'''simple docstring'''



def 			SCREAMING_SNAKE_CASE_			(							__A    :			str	,					__A    :			str  )			->			str:
   _SCREAMING_SNAKE_CASE	=				len(__A  )
   _SCREAMING_SNAKE_CASE	=				len(__A  )
   _SCREAMING_SNAKE_CASE	=				(
       first_str_length if first_str_length > second_str_length else second_str_length
   )
   _SCREAMING_SNAKE_CASE	=				[]
   for char_count in range(__A  ):
      if char_count < first_str_length:
         output_list.append(first_str[char_count]  )
      if char_count < second_str_length:
         output_list.append(second_str[char_count]  )
   return "".join(__A  )


if __name__ == "__main__":
 print(alternative_string_arrange('AB', 'XYZ'), end=' ')

