






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


__UpperCamelCase   :   Tuple      =    logging.get_logger(__name__)

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


class 							__UpperCamelCase     (  _lowerCAmelCase ):
	__snake_case						:Union[str, Any] =							'lxmert'
	__snake_case						:Union[str, Any] =							{}







	def __init__(	self   :				List[str]							,					_lowerCAmelCase   :				Dict=3_0522							,					_lowerCAmelCase   :				List[str]=768							,					_lowerCAmelCase   :				Union[str, Any]=12							,					_lowerCAmelCase   :				Union[str, Any]=9500							,					_lowerCAmelCase   :				Union[str, Any]=1600							,					_lowerCAmelCase   :				Optional[Any]=400							,					_lowerCAmelCase   :				Tuple=3072							,					_lowerCAmelCase   :				List[Any]="gelu"							,					_lowerCAmelCase   :				int=0.1							,					_lowerCAmelCase   :				Dict=0.1							,					_lowerCAmelCase   :				Tuple=512							,					_lowerCAmelCase   :				Tuple=2							,					_lowerCAmelCase   :				Optional[Any]=0.02							,					_lowerCAmelCase   :				List[str]=1e-12							,					_lowerCAmelCase   :				Any=9							,					_lowerCAmelCase   :				Optional[Any]=5							,					_lowerCAmelCase   :				Any=5							,					_lowerCAmelCase   :				Dict=2048							,					_lowerCAmelCase   :				int=4							,					_lowerCAmelCase   :				Optional[Any]=6.67							,					_lowerCAmelCase   :				Optional[Any]=True							,					_lowerCAmelCase   :				int=True							,					_lowerCAmelCase   :				int=True							,					_lowerCAmelCase   :				str=True							,					_lowerCAmelCase   :				Dict=True							,					_lowerCAmelCase   :				int=True							,					_lowerCAmelCase   :				int=True							,					**_lowerCAmelCase   :				Tuple							,					)		->			Dict:
		"""simple docstring"""







		__lowercase   							=	vocab_size
		__lowercase   							=	hidden_size
		__lowercase   							=	num_attention_heads
		__lowercase   							=	hidden_act
		__lowercase   							=	intermediate_size
		__lowercase   							=	hidden_dropout_prob
		__lowercase   							=	attention_probs_dropout_prob
		__lowercase   							=	max_position_embeddings
		__lowercase   							=	type_vocab_size
		__lowercase   							=	initializer_range
		__lowercase   							=	layer_norm_eps
		__lowercase   							=	num_qa_labels
		__lowercase   							=	num_object_labels
		__lowercase   							=	num_attr_labels
		__lowercase   							=	l_layers
		__lowercase   							=	x_layers
		__lowercase   							=	r_layers
		__lowercase   							=	visual_feat_dim
		__lowercase   							=	visual_pos_dim
		__lowercase   							=	visual_loss_normalizer
		__lowercase   							=	task_matched
		__lowercase   							=	task_mask_lm
		__lowercase   							=	task_obj_predict
		__lowercase   							=	task_qa
		__lowercase   							=	visual_obj_loss
		__lowercase   							=	visual_attr_loss
		__lowercase   							=	visual_feat_loss
		__lowercase   							=	{"""vision""": r_layers, """cross_encoder""": x_layers, """language""": l_layers}
		super().__init__(**_lowerCAmelCase      )







'''simple docstring'''


import warnings

from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor


_lowercase  =			logging.get_logger(__name__)
class 						a_				(			UpperCAmelCase__						):




	def __init__(       self     :  Tuple       ,		*__lowerCAmelCase     :  List[str]       ,		**__lowerCAmelCase     :  List[str]      ):
							warnings.warn(
							    'The class VideoMAEFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
							    ' Please use VideoMAEImageProcessor instead.'       ,		__lowerCAmelCase       ,		)
							super().__init__(*__lowerCAmelCase       ,		**__lowerCAmelCase      )

