


'''simple docstring'''





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


UpperCAmelCase__      =							logging.get_logger(__name__)

UpperCAmelCase__      =							{
    '''openbmb/cpm-ant-10b''': '''https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json'''
    # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
}
class 	a__				(				a_      ):





			'''simple docstring'''

			A	:							Tuple							= '''cpmant'''
			def __init__(     self       : Union[str, Any] ,						lowerCAmelCase_       : int = 30_720 ,						lowerCAmelCase_       : int = 4_096 ,						lowerCAmelCase_       : int = 32 ,						lowerCAmelCase_       : int = 128 ,						lowerCAmelCase_       : int = 10_240 ,						lowerCAmelCase_       : int = 48 ,						lowerCAmelCase_       : int = 0.0 ,						lowerCAmelCase_       : int = 512 ,						lowerCAmelCase_       : int = 2_048 ,						lowerCAmelCase_       : int = 1E-6 ,						lowerCAmelCase_       : float = 1.0 ,						lowerCAmelCase_       : int = 32 ,						lowerCAmelCase_       : int = 32 ,						lowerCAmelCase_       : int = 32 ,						lowerCAmelCase_       : bool = True ,						**lowerCAmelCase_       : Optional[Any] ,						)			->		str:
						super().__init__(**lowerCAmelCase_  )
						__A=  prompt_types
						__A=  prompt_length
						__A=  segment_types
						__A=  hidden_size
						__A=  num_attention_heads
						__A=  dim_head
						__A=  dim_ff
						__A=  num_hidden_layers
						__A=  position_bias_num_buckets
						__A=  position_bias_max_distance
						__A=  dropout_p
						__A=  eps
						__A=  use_cache
						__A=  vocab_size
						__A=  init_std







'''simple docstring'''





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


UpperCAmelCase__      =							logging.get_logger(__name__)

UpperCAmelCase__      =							{
    '''dandelin/vilt-b32-mlm''': '''https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json'''
}
class 	a__				(				a_      ):





			'''simple docstring'''

			A	:							Dict							= '''vilt'''
			def __init__(     self       : str ,						lowerCAmelCase_       : Tuple=30_522 ,						lowerCAmelCase_       : List[Any]=2 ,						lowerCAmelCase_       : Optional[Any]=2 ,						lowerCAmelCase_       : Union[str, Any]=40 ,						lowerCAmelCase_       : str=768 ,						lowerCAmelCase_       : Tuple=12 ,						lowerCAmelCase_       : List[Any]=12 ,						lowerCAmelCase_       : int=3_072 ,						lowerCAmelCase_       : List[Any]="gelu" ,						lowerCAmelCase_       : int=0.0 ,						lowerCAmelCase_       : str=0.0 ,						lowerCAmelCase_       : Optional[Any]=0.02 ,						lowerCAmelCase_       : Union[str, Any]=1E-12 ,						lowerCAmelCase_       : Dict=384 ,						lowerCAmelCase_       : Optional[int]=32 ,						lowerCAmelCase_       : Optional[Any]=3 ,						lowerCAmelCase_       : str=True ,						lowerCAmelCase_       : List[Any]=-1 ,						lowerCAmelCase_       : Union[str, Any]=False ,						lowerCAmelCase_       : str=-1 ,						**lowerCAmelCase_       : Any ,						)			->		Tuple:
						super().__init__(tie_word_embeddings=lowerCAmelCase_ ,						**lowerCAmelCase_  )

						__A=  vocab_size
						__A=  type_vocab_size
						__A=  modality_type_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=  layer_norm_eps

						__A=  image_size
						__A=  patch_size
						__A=  num_channels
						__A=  qkv_bias
						__A=  max_image_length
						__A=  num_images



