





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


__lowerCAmelCase :Optional[Any]     =    logging.get_logger(__name__)

__lowerCAmelCase :Optional[Any]     =    {
    'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}






class        _a(    _A    ):
		lowerCamelCase__     :str   				=		'lxmert'
		lowerCamelCase__     :Dict   				=		{}







		def __init__(    self ,						__snake_case=3_0_5_2_2 ,						__snake_case=7_6_8 ,						__snake_case=1_2 ,						__snake_case=9_5_0_0 ,						__snake_case=1_6_0_0 ,						__snake_case=4_0_0 ,						__snake_case=3_0_7_2 ,						__snake_case="gelu" ,						__snake_case=0.1 ,						__snake_case=0.1 ,						__snake_case=5_1_2 ,						__snake_case=2 ,						__snake_case=0.02 ,						__snake_case=1E-12 ,						__snake_case=9 ,						__snake_case=5 ,						__snake_case=5 ,						__snake_case=2_0_4_8 ,						__snake_case=4 ,						__snake_case=6.67 ,						__snake_case=True ,						__snake_case=True ,						__snake_case=True ,						__snake_case=True ,						__snake_case=True ,						__snake_case=True ,						__snake_case=True ,						**__snake_case ,						)      ->      Optional[Any]:


							'''simple docstring'''

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






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


__lowerCAmelCase :Tuple     =    logging.get_logger(__name__)

__lowerCAmelCase :int     =    {
    'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}






class        _a(    __A    ):
		lowerCamelCase__     :Optional[Any]   				=		'timesformer'







		def __init__(    self ,						__snake_case=2_2_4 ,						__snake_case=1_6 ,						__snake_case=3 ,						__snake_case=8 ,						__snake_case=7_6_8 ,						__snake_case=1_2 ,						__snake_case=1_2 ,						__snake_case=3_0_7_2 ,						__snake_case="gelu" ,						__snake_case=0.0 ,						__snake_case=0.0 ,						__snake_case=0.02 ,						__snake_case=1E-6 ,						__snake_case=True ,						__snake_case="divided_space_time" ,						__snake_case=0 ,						**__snake_case ,						)      ->      str:


							'''simple docstring'''

							super().__init__(**__snake_case				)

							_snake_case       :					Optional[Any]				       =   image_size
							_snake_case       :					Optional[int]				       =   patch_size
							_snake_case       :					str				       =   num_channels
							_snake_case       :					Tuple				       =   num_frames

							_snake_case       :					Union[str, Any]				       =   hidden_size
							_snake_case       :					Optional[int]				       =   num_hidden_layers
							_snake_case       :					List[Any]				       =   num_attention_heads
							_snake_case       :					Optional[int]				       =   intermediate_size
							_snake_case       :					List[str]				       =   hidden_act
							_snake_case       :					Optional[int]				       =   hidden_dropout_prob
							_snake_case       :					Optional[Any]				       =   attention_probs_dropout_prob
							_snake_case       :					Dict				       =   initializer_range
							_snake_case       :					Optional[int]				       =   layer_norm_eps
							_snake_case       :					str				       =   qkv_bias

							_snake_case       :					List[str]				       =   attention_type
							_snake_case       :					Optional[int]				       =   drop_path_rate