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


A     :  List[str]					     =       logging.get_logger(__name__)

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


class   lowerCamelCase					(SCREAMING_SNAKE_CASE__					):
  """simple docstring"""







  lowerCamelCase__     =						'''lxmert'''
  lowerCamelCase__     =						{}







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



import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


A     :  str					     =       logging.getLogger(__name__)


@dataclass
class   lowerCamelCase					(SCREAMING_SNAKE_CASE__					):
  """simple docstring"""







  lowerCamelCase__     =						field(
      default=0.0  ,      metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}					)
  lowerCamelCase__     =						field(default=SCREAMING_SNAKE_CASE__  ,      metadata={'''help''': '''Whether to SortishSamler or not.'''}					)
  lowerCamelCase__     =						field(
      default=SCREAMING_SNAKE_CASE__  ,      metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}					)
  lowerCamelCase__     =						field(default=SCREAMING_SNAKE_CASE__  ,      metadata={'''help''': '''whether to use adafactor'''}					)
  lowerCamelCase__     =						field(
      default=SCREAMING_SNAKE_CASE__  ,      metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}					)
  lowerCamelCase__     =						field(
      default=SCREAMING_SNAKE_CASE__  ,      metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}					)
  lowerCamelCase__     =						field(default=SCREAMING_SNAKE_CASE__  ,      metadata={'''help''': '''Dropout probability. Goes into model.config.'''}					)
  lowerCamelCase__     =						field(
      default=SCREAMING_SNAKE_CASE__  ,      metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}					)
  lowerCamelCase__     =						field(
      default='''linear'''  ,      metadata={'''help''': f"Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()					)}"}  ,      )


