'''simple docstring'''

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


UpperCamelCase__     :	str				=			logging.get_logger(__name__)

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


class 				_lowercase	(      lowerCAmelCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      List[Any]      							=   '''lxmert'''
      UpperCAmelCase_      :      Tuple      							=   {}




      def __init__(				self					,lowerCamelCase_=30522					,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_					,)			->			Optional[int]:



         '''simple docstring'''



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





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCamelCase__     :	Union[str, Any]				=			{'tokenization_byt5': ['ByT5Tokenizer']}


if TYPE_CHECKING:
  from .tokenization_byta import ByTaTokenizer
else:
  import sys

  UpperCamelCase__     :	List[str]				=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




