code: 
  
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  __UpperCAmelCase      = logging.get_logger(__name__)
  
  __UpperCAmelCase      = {
      '''facebook/opt-125m''': '''https://huggingface.co/facebook/opt-125m/blob/main/config.json''',
      '''facebook/opt-350m''': '''https://huggingface.co/facebook/opt-350m/blob/main/config.json''',
      '''facebook/opt-1.3b''': '''https://huggingface.co/facebook/opt-1.3b/blob/main/config.json''',
      '''facebook/opt-2.7b''': '''https://huggingface.co/facebook/opt-2.7b/blob/main/config.json''',
      '''facebook/opt-6.7b''': '''https://huggingface.co/facebook/opt-6.7b/blob/main/config.json''',
      '''facebook/opt-13b''': '''https://huggingface.co/facebook/opt-13b/blob/main/config.json''',
  }
  
  
  
  class        lowerCAmelCase_	(						a__							):
         UpperCAmelCase__       :      List[Any]       =						"opt"
         UpperCAmelCase__       :      Tuple       =						["past_key_values"]
         def __init__(    self,    SCREAMING_SNAKE_CASE_=5_0272,    SCREAMING_SNAKE_CASE_=768,    SCREAMING_SNAKE_CASE_=12,    SCREAMING_SNAKE_CASE_=3072,    SCREAMING_SNAKE_CASE_=2048,    SCREAMING_SNAKE_CASE_=True,    SCREAMING_SNAKE_CASE_=False,    SCREAMING_SNAKE_CASE_=None,    SCREAMING_SNAKE_CASE_=0.1,    SCREAMING_SNAKE_CASE_=0.0,    SCREAMING_SNAKE_CASE_=12,    SCREAMING_SNAKE_CASE_="relu",    SCREAMING_SNAKE_CASE_=0.0,    SCREAMING_SNAKE_CASE_=0.02,    SCREAMING_SNAKE_CASE_=True,    SCREAMING_SNAKE_CASE_=1,    SCREAMING_SNAKE_CASE_=2,    SCREAMING_SNAKE_CASE_=2,    SCREAMING_SNAKE_CASE_=True,    SCREAMING_SNAKE_CASE_=True,    **SCREAMING_SNAKE_CASE_,    )  ->	Tuple:
            super().__init__(
                pad_token_id=SCREAMING_SNAKE_CASE_,    bos_token_id=SCREAMING_SNAKE_CASE_,    eos_token_id=SCREAMING_SNAKE_CASE_,    **SCREAMING_SNAKE_CASE_,    )
            UpperCamelCase					:						Dict					=			vocab_size
            UpperCamelCase					:						Tuple					=			max_position_embeddings
            UpperCamelCase					:						Union[str, Any]					=			num_attention_heads
            UpperCamelCase					:						Any					=			word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
            UpperCamelCase					:						Dict					=			ffn_dim
            UpperCamelCase					:						int					=			hidden_size
            UpperCamelCase					:						Union[str, Any]					=			num_hidden_layers
            UpperCamelCase					:						Tuple					=			dropout
            UpperCamelCase					:						Tuple					=			attention_dropout
            UpperCamelCase					:						Any					=			activation_function
            UpperCamelCase					:						Dict					=			init_std
            UpperCamelCase					:						Optional[Any]					=			layerdrop
            UpperCamelCase					:						str					=			use_cache
            UpperCamelCase					:						Any					=			do_layer_norm_before
            # We keep these variables at `True` for backward compatibility.
            UpperCamelCase					:						Optional[int]					=			enable_bias
            UpperCamelCase					:						str					=			layer_norm_elementwise_affine
  
            # Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
            # with checkpoints that have been fine-tuned before transformers v4.20.1
            # see https://github.com/facebookresearch/metaseq/pull/164
            UpperCamelCase					:						Any					=			_remove_final_layer_norm
  
  
  
  
style_context: 
  
  
  
  import json
  import logging
  import os
  import subprocess
  from argparse import ArgumentParser
  
  
  __UpperCAmelCase      = logging.getLogger(__name__)
  def 	UpperCamelCase			(     )			->  List[str]:
     UpperCamelCase					:						Union[str, Any]					=			ArgumentParser()
     UpperCamelCase			,  UpperCamelCase					:						Optional[int]					=			parser.parse_known_args()
     for arg in unknown:
        if arg.startswith(('-', '--')			):
           parser.add_argument(arg.split('='			)[0]			)
  
     return parser.parse_args()
  def 	UpperCamelCase			(     )			->  Optional[Any]:
     UpperCamelCase					:						int					=			parse_args()
     UpperCamelCase					:						Dict					=			8888
     UpperCamelCase					:						Union[str, Any]					=			int(os.environ['SM_NUM_GPUS']			)
     UpperCamelCase					:						Optional[Any]					=			json.loads(os.environ['SM_HOSTS']			)
     UpperCamelCase					:						Dict					=			len(snake_case__			)
     UpperCamelCase					:						int					=			os.environ['SM_CURRENT_HOST']
     UpperCamelCase					:						List[str]					=			hosts.index(snake_case__			)
     UpperCamelCase					:						Optional[Any]					=			'INFO'
  
     if num_nodes > 1:
        UpperCamelCase					:						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:
        UpperCamelCase					:						Any					=			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(snake_case__ ,  shell=snake_case__			)
     except Exception as e:
        logger.info(snake_case__			)
  
  
  if __name__ == "__main__":
      main()
  
  
  
  