





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


_UpperCAmelCase             =							logging.get_logger(__name__)

_UpperCAmelCase             =							{
    'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}






class        snake_case_    (		__lowercase						):
  A_      							=   'lxmert'
  A_      							=   {}






  def __init__(							self			:					Any       ,  _snake_case			:					List[str]=30522       ,  _snake_case			:					Dict=768       ,  _snake_case			:					Tuple=12       ,  _snake_case			:					List[str]=9500       ,  _snake_case			:					Any=1600       ,  _snake_case			:					Union[str, Any]=400       ,  _snake_case			:					Optional[int]=3072       ,  _snake_case			:					Tuple="gelu"       ,  _snake_case			:					List[str]=0.1       ,  _snake_case			:					List[Any]=0.1       ,  _snake_case			:					int=512       ,  _snake_case			:					Dict=2       ,  _snake_case			:					List[Any]=0.02       ,  _snake_case			:					List[Any]=1E-12       ,  _snake_case			:					str=9       ,  _snake_case			:					List[str]=5       ,  _snake_case			:					List[Any]=5       ,  _snake_case			:					Any=2048       ,  _snake_case			:					Tuple=4       ,  _snake_case			:					int=6.67       ,  _snake_case			:					Optional[Any]=True       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Optional[Any]=True       ,  _snake_case			:					Optional[Any]=True       ,  _snake_case			:					List[Any]=True       ,  _snake_case			:					Optional[Any]=True       ,  _snake_case			:					Optional[Any]=True       ,  **_snake_case			:					Optional[int]       ,  )->Optional[int]:






   '''simple docstring'''

   __lowerCAmelCase					:	Union[str, Any]      =       vocab_size
   __lowerCAmelCase					:	str      =       hidden_size
   __lowerCAmelCase					:	str      =       num_attention_heads
   __lowerCAmelCase					:	Union[str, Any]      =       hidden_act
   __lowerCAmelCase					:	int      =       intermediate_size
   __lowerCAmelCase					:	Any      =       hidden_dropout_prob
   __lowerCAmelCase					:	Tuple      =       attention_probs_dropout_prob
   __lowerCAmelCase					:	List[str]      =       max_position_embeddings
   __lowerCAmelCase					:	Dict      =       type_vocab_size
   __lowerCAmelCase					:	str      =       initializer_range
   __lowerCAmelCase					:	List[Any]      =       layer_norm_eps
   __lowerCAmelCase					:	Dict      =       num_qa_labels
   __lowerCAmelCase					:	List[str]      =       num_object_labels
   __lowerCAmelCase					:	Optional[int]      =       num_attr_labels
   __lowerCAmelCase					:	Dict      =       l_layers
   __lowerCAmelCase					:	Union[str, Any]      =       x_layers
   __lowerCAmelCase					:	Dict      =       r_layers
   __lowerCAmelCase					:	Tuple      =       visual_feat_dim
   __lowerCAmelCase					:	str      =       visual_pos_dim
   __lowerCAmelCase					:	str      =       visual_loss_normalizer
   __lowerCAmelCase					:	Optional[int]      =       task_matched
   __lowerCAmelCase					:	str      =       task_mask_lm
   __lowerCAmelCase					:	Union[str, Any]      =       task_obj_predict
   __lowerCAmelCase					:	Any      =       task_qa
   __lowerCAmelCase					:	Dict      =       visual_obj_loss
   __lowerCAmelCase					:	Optional[int]      =       visual_attr_loss
   __lowerCAmelCase					:	List[str]      =       visual_feat_loss
   __lowerCAmelCase					:	Any      =       {"""vision""": r_layers, """cross_encoder""": x_layers, """language""": l_layers}
   super().__init__(**_snake_case      )






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


_UpperCAmelCase             =							logging.get_logger(__name__)

_UpperCAmelCase             =							{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class        snake_case_    (		__lowercase						):
  A_      							=   'biogpt'






  def __init__(							self			:					int       ,  _snake_case			:					Any=42384       ,  _snake_case			:					Any=1024       ,  _snake_case			:					List[Any]=24       ,  _snake_case			:					Any=16       ,  _snake_case			:					List[str]=4096       ,  _snake_case			:					Dict="gelu"       ,  _snake_case			:					Tuple=0.1       ,  _snake_case			:					str=0.1       ,  _snake_case			:					Tuple=1024       ,  _snake_case			:					Tuple=0.02       ,  _snake_case			:					Tuple=1E-12       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Any=0.0       ,  _snake_case			:					Tuple=0.0       ,  _snake_case			:					str=1       ,  _snake_case			:					Dict=0       ,  _snake_case			:					str=2       ,  **_snake_case			:					Union[str, Any]       ,  )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       vocab_size
   __lowerCAmelCase					:	Dict      =       max_position_embeddings
   __lowerCAmelCase					:	str      =       hidden_size
   __lowerCAmelCase					:	Dict      =       num_hidden_layers
   __lowerCAmelCase					:	List[Any]      =       num_attention_heads
   __lowerCAmelCase					:	Optional[Any]      =       intermediate_size
   __lowerCAmelCase					:	int      =       hidden_act
   __lowerCAmelCase					:	Any      =       hidden_dropout_prob
   __lowerCAmelCase					:	Any      =       attention_probs_dropout_prob
   __lowerCAmelCase					:	Any      =       initializer_range
   __lowerCAmelCase					:	int      =       layer_norm_eps
   __lowerCAmelCase					:	Optional[int]      =       scale_embedding
   __lowerCAmelCase					:	List[Any]      =       use_cache
   __lowerCAmelCase					:	str      =       layerdrop
   __lowerCAmelCase					:	Dict      =       activation_dropout
   super().__init__(pad_token_id=_snake_case       ,  bos_token_id=_snake_case       ,  eos_token_id=_snake_case       ,  **_snake_case      )