code: 
  
  import json
  import logging
  import os
  import subprocess
  from argparse import ArgumentParser
  
  
  UpperCAmelCase_       :				Any		   =      logging.getLogger(__name__)
  def        __SCREAMING_SNAKE_CASE    (      )				->							List[Any]:
  	__A   : List[str]								= ArgumentParser()
  	__A						,							__A   : str								= parser.parse_known_args()
  	for arg in unknown:
  		if arg.startswith(("""-""", """--""")					):
  			parser.add_argument(arg.split("""="""					)[0]					)
  
  	return parser.parse_args()
  def        __SCREAMING_SNAKE_CASE    (      )				->							Dict:
  	__A   : Any								= parse_args()
  	__A   : Union[str, Any]								= 8888
  	__A   : List[Any]								= int(os.environ["""SM_NUM_GPUS"""]					)
  	__A   : Tuple								= json.loads(os.environ["""SM_HOSTS"""]					)
  	__A   : List[str]								= len(a__					)
  	__A   : Dict								= os.environ["""SM_CURRENT_HOST"""]
  	__A   : Optional[Any]								= hosts.index(a__					)
  	__A   : Optional[int]								= """INFO"""
  
  	if num_nodes > 1:
  		__A   : List[Any]								= f"""python -m torch.distributed.launch \
                  --nnodes={num_nodes}  \
                  --node_rank={rank}  \
                  --nproc_per_node={num_gpus}  \
                  --master_addr={hosts[0]}  \
                  --master_port={port} \
                  ./run_glue.py \
                  {"".join(["nested fstring" for parameter,value in args.__dict__.items()]					)}"""
  	else:
  		__A   : Dict								= f"""python -m torch.distributed.launch \
              --nproc_per_node={num_gpus}  \
              ./run_glue.py \
              {"".join(["nested fstring" for parameter,value in args.__dict__.items()]					)}"""
  	try:
  		subprocess.run(a__ ,shell=a__					)
  	except Exception as e:
  		logger.info(a__					)
  
  
  if __name__ == "__main__":
  			main()
  
  
  
  
  
  
style_context: 
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  UpperCAmelCase_       :				Optional[Any]		   =      logging.get_logger(__name__)
  
  UpperCAmelCase_       :				List[str]		   =      {
      '''uw-madison/nystromformer-512''': '''https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json''',
      # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
  }
  
  
  
  
  
  
  class     lowerCamelCase_			(  _lowercase  ):
  	_lowercase		:      Optional[Any]    				=							'''nystromformer'''
  
  
  
  
  	def __init__(    self	:    Optional[Any]				,			__A	:    Optional[Any]=3_0000				,			__A	:    Optional[int]=768				,			__A	:    List[str]=12				,			__A	:    str=12				,			__A	:    Tuple=3072				,			__A	:    List[Any]="gelu_new"				,			__A	:    Dict=0.1				,			__A	:    Optional[int]=0.1				,			__A	:    int=510				,			__A	:    Union[str, Any]=2				,			__A	:    Optional[int]=64				,			__A	:    str=64				,			__A	:    List[str]=65				,			__A	:    Tuple=False				,			__A	:    List[str]=0.0_2				,			__A	:    Tuple=1e-5				,			__A	:    List[str]=1				,			__A	:    int=0				,			__A	:    Tuple=2				,			**__A	:    Dict				,			):
  		__A   : str								= vocab_size
  		__A   : Union[str, Any]								= max_position_embeddings
  		__A   : Optional[int]								= hidden_size
  		__A   : Optional[int]								= num_hidden_layers
  		__A   : List[Any]								= num_attention_heads
  		__A   : Dict								= intermediate_size
  		__A   : Union[str, Any]								= hidden_act
  		__A   : int								= hidden_dropout_prob
  		__A   : Tuple								= attention_probs_dropout_prob
  		__A   : Optional[Any]								= initializer_range
  		__A   : int								= type_vocab_size
  		__A   : Optional[int]								= segment_means_seq_len
  		__A   : List[str]								= num_landmarks
  		__A   : Dict								= conv_kernel_size
  		__A   : Union[str, Any]								= inv_coeff_init_option
  		__A   : Union[str, Any]								= layer_norm_eps
  		super().__init__(pad_token_id=__A				,			bos_token_id=__A				,			eos_token_id=__A				,			**__A       )
  
  
  
  
  
  