

'''simple docstring'''



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


UpperCAmelCase					:			int       =	logging.get_logger(__name__)

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







class 		lowerCAmelCase__  ( a   ):



 """simple docstring"""



 lowerCAmelCase__       = "lxmert"
 lowerCAmelCase__       = {}
 def __init__(						self   :			List[Any]   ,				__SCREAMING_SNAKE_CASE   :			List[str]=30_522   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=768   ,				__SCREAMING_SNAKE_CASE   :			List[Any]=12   ,				__SCREAMING_SNAKE_CASE   :			Any=9_500   ,				__SCREAMING_SNAKE_CASE   :			int=1_600   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=400   ,				__SCREAMING_SNAKE_CASE   :			Dict=3_072   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]="gelu"   ,				__SCREAMING_SNAKE_CASE   :			Optional[int]=0.1   ,				__SCREAMING_SNAKE_CASE   :			List[Any]=0.1   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=512   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=2   ,				__SCREAMING_SNAKE_CASE   :			List[str]=0.02   ,				__SCREAMING_SNAKE_CASE   :			str=1E-12   ,				__SCREAMING_SNAKE_CASE   :			int=9   ,				__SCREAMING_SNAKE_CASE   :			Optional[int]=5   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=5   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=2_048   ,				__SCREAMING_SNAKE_CASE   :			List[Any]=4   ,				__SCREAMING_SNAKE_CASE   :			Tuple=6.67   ,				__SCREAMING_SNAKE_CASE   :			str=True   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=True   ,				__SCREAMING_SNAKE_CASE   :			str=True   ,				__SCREAMING_SNAKE_CASE   :			List[str]=True   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=True   ,				__SCREAMING_SNAKE_CASE   :			Any=True   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=True   ,				**__SCREAMING_SNAKE_CASE   :			int   ,				)    ->					List[str]:


      """simple docstring"""




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









'''simple docstring'''



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


UpperCAmelCase					:			Tuple       =	logging.get_logger(__name__)

UpperCAmelCase					:			Any       =	{'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}







class 		lowerCAmelCase__  ( a   ):



 """simple docstring"""



 lowerCAmelCase__       = "ctrl"
 lowerCAmelCase__       = ["past_key_values"]
 lowerCAmelCase__       = {
     "max_position_embeddings": "n_positions",
     "hidden_size": "n_embd",
     "num_attention_heads": "n_head",
     "num_hidden_layers": "n_layer",
 }
 def __init__(						self   :			Tuple   ,				__SCREAMING_SNAKE_CASE   :			Tuple=246_534   ,				__SCREAMING_SNAKE_CASE   :			str=256   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=1_280   ,				__SCREAMING_SNAKE_CASE   :			Dict=8_192   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=48   ,				__SCREAMING_SNAKE_CASE   :			Dict=16   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=0.1   ,				__SCREAMING_SNAKE_CASE   :			str=0.1   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=1E-6   ,				__SCREAMING_SNAKE_CASE   :			Tuple=0.02   ,				__SCREAMING_SNAKE_CASE   :			Tuple=True   ,				**__SCREAMING_SNAKE_CASE   :			Union[str, Any]   ,				)    ->					Tuple:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = vocab_size
      __SCREAMING_SNAKE_CASE      = n_positions
      __SCREAMING_SNAKE_CASE      = n_embd
      __SCREAMING_SNAKE_CASE      = n_layer
      __SCREAMING_SNAKE_CASE      = n_head
      __SCREAMING_SNAKE_CASE      = dff
      __SCREAMING_SNAKE_CASE      = resid_pdrop
      __SCREAMING_SNAKE_CASE      = embd_pdrop
      __SCREAMING_SNAKE_CASE      = layer_norm_epsilon
      __SCREAMING_SNAKE_CASE      = initializer_range

      __SCREAMING_SNAKE_CASE      = use_cache

      super().__init__(**__SCREAMING_SNAKE_CASE     )






