





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


_lowerCamelCase 					=      logging.get_logger(__name__)

_lowerCamelCase 					=      {
    'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}




class 	UpperCamelCase_							(  UpperCamelCase__     ):
							lowerCamelCase_							     =       "vit_mae"


							def __init__(				self     :int				,					__A     :str=768				,					__A     :str=12				,					__A     :List[Any]=12				,					__A     :Optional[Any]=3072				,					__A     :Optional[int]="gelu"				,					__A     :List[str]=0.0				,					__A     :Optional[int]=0.0				,					__A     :Dict=0.0_2				,					__A     :List[str]=1E-12				,					__A     :List[Any]=224				,					__A     :Any=16				,					__A     :Tuple=3				,					__A     :Optional[Any]=True				,					__A     :int=16				,					__A     :int=512				,					__A     :int=8				,					__A     :List[str]=2048				,					__A     :Any=0.7_5				,					__A     :Dict=False				,					**__A     :int				,					) -> List[str]:



									"""simple docstring"""



									super().__init__(**__A		)

									SCREAMING_SNAKE_CASE__								=   hidden_size
									SCREAMING_SNAKE_CASE__								=   num_hidden_layers
									SCREAMING_SNAKE_CASE__								=   num_attention_heads
									SCREAMING_SNAKE_CASE__								=   intermediate_size
									SCREAMING_SNAKE_CASE__								=   hidden_act
									SCREAMING_SNAKE_CASE__								=   hidden_dropout_prob
									SCREAMING_SNAKE_CASE__								=   attention_probs_dropout_prob
									SCREAMING_SNAKE_CASE__								=   initializer_range
									SCREAMING_SNAKE_CASE__								=   layer_norm_eps
									SCREAMING_SNAKE_CASE__								=   image_size
									SCREAMING_SNAKE_CASE__								=   patch_size
									SCREAMING_SNAKE_CASE__								=   num_channels
									SCREAMING_SNAKE_CASE__								=   qkv_bias
									SCREAMING_SNAKE_CASE__								=   decoder_num_attention_heads
									SCREAMING_SNAKE_CASE__								=   decoder_hidden_size
									SCREAMING_SNAKE_CASE__								=   decoder_num_hidden_layers
									SCREAMING_SNAKE_CASE__								=   decoder_intermediate_size
									SCREAMING_SNAKE_CASE__								=   mask_ratio
									SCREAMING_SNAKE_CASE__								=   norm_pix_loss







import warnings

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


_SCREAMING_SNAKE_CASE   =  logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   =  {
    "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}






class 					SCREAMING_SNAKE_CASE_  (       _a ):
       """simple docstring"""


       __lowerCAmelCase    :		List[str]					='''mvp'''
       __lowerCAmelCase    :		List[Any]					=['''past_key_values''']
       __lowerCAmelCase    :		Optional[Any]					={'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}





       def __init__(				self	:Any,      snake_case	:Any=5_0267,      snake_case	:List[str]=1024,      snake_case	:List[str]=12,      snake_case	:List[Any]=4096,      snake_case	:List[Any]=16,      snake_case	:Optional[int]=12,      snake_case	:Optional[int]=4096,      snake_case	:List[str]=16,      snake_case	:Optional[Any]=0.0,      snake_case	:Tuple=0.0,      snake_case	:str="gelu",      snake_case	:int=1024,      snake_case	:Any=0.1,      snake_case	:Dict=0.0,      snake_case	:Optional[Any]=0.0,      snake_case	:int=0.0_2,      snake_case	:Union[str, Any]=0.0,      snake_case	:Tuple=False,      snake_case	:Optional[int]=True,      snake_case	:Any=1,      snake_case	:Union[str, Any]=0,      snake_case	:Optional[Any]=2,      snake_case	:Union[str, Any]=True,      snake_case	:Tuple=2,      snake_case	:Any=2,      snake_case	:List[Any]=False,      snake_case	:Optional[int]=100,      snake_case	:Union[str, Any]=800,      **snake_case	:Tuple,      ):



          """simple docstring"""

          _lowercase              =vocab_size
          _lowercase              =max_position_embeddings
          _lowercase              =d_model
          _lowercase              =encoder_ffn_dim
          _lowercase              =encoder_layers
          _lowercase              =encoder_attention_heads
          _lowercase              =decoder_ffn_dim
          _lowercase              =decoder_layers
          _lowercase              =decoder_attention_heads
          _lowercase              =dropout
          _lowercase              =attention_dropout
          _lowercase              =activation_dropout
          _lowercase              =activation_function
          _lowercase              =init_std
          _lowercase              =encoder_layerdrop
          _lowercase              =decoder_layerdrop
          _lowercase              =classifier_dropout
          _lowercase              =use_cache
          _lowercase              =encoder_layers
          _lowercase              =scale_embedding  # scale factor will be sqrt(d_model) if True
          _lowercase              =use_prompt
          _lowercase              =prompt_length
          _lowercase              =prompt_mid_dim

          super().__init__(
              pad_token_id=snake_case,      bos_token_id=snake_case,      eos_token_id=snake_case,      is_encoder_decoder=snake_case,      decoder_start_token_id=snake_case,      forced_eos_token_id=snake_case,      **snake_case,      )

          if self.forced_bos_token_id is None and kwargs.get('force_bos_token_to_be_generated',      snake_case):
             _lowercase              =self.bos_token_id
             warnings.warn(
                 f'''Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '''
                 'The config can simply be saved and uploaded again to be fixed.')


