





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      UpperCamelCase_						(					A_   ):
     lowerCAmelCase_							=		'''lxmert'''
     lowerCAmelCase_							=		{}




     def __init__(						self			,  lowerCAmelCase_=3_0522			,  lowerCAmelCase_=768			,  lowerCAmelCase_=12			,  lowerCAmelCase_=9500			,  lowerCAmelCase_=1600			,  lowerCAmelCase_=400			,  lowerCAmelCase_=3072			,  lowerCAmelCase_="gelu"			,  lowerCAmelCase_=0.1			,  lowerCAmelCase_=0.1			,  lowerCAmelCase_=512			,  lowerCAmelCase_=2			,  lowerCAmelCase_=0.02			,  lowerCAmelCase_=1E-12			,  lowerCAmelCase_=9			,  lowerCAmelCase_=5			,  lowerCAmelCase_=5			,  lowerCAmelCase_=2048			,  lowerCAmelCase_=4			,  lowerCAmelCase_=6.67			,  lowerCAmelCase_=True			,  lowerCAmelCase_=True			,  lowerCAmelCase_=True			,  lowerCAmelCase_=True			,  lowerCAmelCase_=True			,  lowerCAmelCase_=True			,  lowerCAmelCase_=True			,  **lowerCAmelCase_			,  )						->							int:
          _snake_case													=			vocab_size
          _snake_case													=			hidden_size
          _snake_case													=			num_attention_heads
          _snake_case													=			hidden_act
          _snake_case													=			intermediate_size
          _snake_case													=			hidden_dropout_prob
          _snake_case													=			attention_probs_dropout_prob
          _snake_case													=			max_position_embeddings
          _snake_case													=			type_vocab_size
          _snake_case													=			initializer_range
          _snake_case													=			layer_norm_eps
          _snake_case													=			num_qa_labels
          _snake_case													=			num_object_labels
          _snake_case													=			num_attr_labels
          _snake_case													=			l_layers
          _snake_case													=			x_layers
          _snake_case													=			r_layers
          _snake_case													=			visual_feat_dim
          _snake_case													=			visual_pos_dim
          _snake_case													=			visual_loss_normalizer
          _snake_case													=			task_matched
          _snake_case													=			task_mask_lm
          _snake_case													=			task_obj_predict
          _snake_case													=			task_qa
          _snake_case													=			visual_obj_loss
          _snake_case													=			visual_attr_loss
          _snake_case													=			visual_feat_loss
          _snake_case													=			{'vision': r_layers, 'cross_encoder': x_layers, 'language': l_layers}
          super().__init__(**_lowerCamelCase					)










import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


UpperCAmelCase_ 							=       logging.get_logger(__name__)
class      UpperCamelCase_						(					_lowerCamelCase   ):




					def __init__(						self			,  *lowerCAmelCase_			,  **lowerCAmelCase_					)						->							None:
										warnings.warn(
										    'The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
										    ' use FlavaImageProcessor instead.'			,  lowerCAmelCase_			,  )
										super().__init__(*lowerCAmelCase_			,  **lowerCAmelCase_					)



