






"""simple docstring"""



from typing import List, Union

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


a  :						Dict					       =							logging.get_logger(__name__)

a  :						Optional[Any]					       =							{
    '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
    # See all LED models at https://huggingface.co/models?filter=led
}


class 	_UpperCamelCase ( __UpperCamelCase							):



    '''simple docstring'''


    __lowercase    :   Optional[int]											=						'led'
    __lowercase    :   Dict											=						{
        'num_attention_heads': 'encoder_attention_heads',
        'hidden_size': 'd_model',
        'attention_probs_dropout_prob': 'attention_dropout',
        'initializer_range': 'init_std',
    }


    def __init__(      self   ,			__lowercase=50265   ,			__lowercase=16384   ,			__lowercase=1024   ,			__lowercase=12   ,			__lowercase=4096   ,			__lowercase=16   ,			__lowercase=12   ,			__lowercase=4096   ,			__lowercase=16   ,			__lowercase=0.0   ,			__lowercase=0.0   ,			__lowercase=True   ,			__lowercase=True   ,			__lowercase="gelu"   ,			__lowercase=1024   ,			__lowercase=0.1   ,			__lowercase=0.0   ,			__lowercase=0.0   ,			__lowercase=0.02   ,			__lowercase=2   ,			__lowercase=0.0   ,			__lowercase=1   ,			__lowercase=0   ,			__lowercase=2   ,			__lowercase = 512   ,			**__lowercase   ,			):
     UpperCAmelCase__ 						=				vocab_size
     UpperCAmelCase__ 						=				max_encoder_position_embeddings
     UpperCAmelCase__ 						=				max_decoder_position_embeddings
     UpperCAmelCase__ 						=				d_model
     UpperCAmelCase__ 						=				encoder_ffn_dim
     UpperCAmelCase__ 						=				encoder_layers
     UpperCAmelCase__ 						=				encoder_attention_heads
     UpperCAmelCase__ 						=				decoder_ffn_dim
     UpperCAmelCase__ 						=				decoder_layers
     UpperCAmelCase__ 						=				decoder_attention_heads
     UpperCAmelCase__ 						=				dropout
     UpperCAmelCase__ 						=				attention_dropout
     UpperCAmelCase__ 						=				activation_dropout
     UpperCAmelCase__ 						=				activation_function
     UpperCAmelCase__ 						=				init_std
     UpperCAmelCase__ 						=				encoder_layerdrop
     UpperCAmelCase__ 						=				decoder_layerdrop
     UpperCAmelCase__ 						=				classifier_dropout
     UpperCAmelCase__ 						=				use_cache
     UpperCAmelCase__ 						=				encoder_layers
     UpperCAmelCase__ 						=				attention_window

     super().__init__(
         pad_token_id=__lowercase   ,			bos_token_id=__lowercase   ,			eos_token_id=__lowercase   ,			is_encoder_decoder=__lowercase   ,			decoder_start_token_id=__lowercase   ,			**__lowercase   ,			)











"""simple docstring"""



import json
import logging
import os
import subprocess
from argparse import ArgumentParser


a  :						Dict					       =							logging.getLogger(__name__)




def       snake_case__		(   )    ->Any:
 UpperCAmelCase__ 						=				ArgumentParser()
 UpperCAmelCase__						,	UpperCAmelCase__ 						=				parser.parse_known_args()
 for arg in unknown:
  if arg.startswith(("""-""", """--""")			):
   parser.add_argument(arg.split("""="""			)[0]			)

 return parser.parse_args()




def       snake_case__		(   )    ->List[Any]:
 UpperCAmelCase__ 						=				parse_args()
 UpperCAmelCase__ 						=				8_8_8_8
 UpperCAmelCase__ 						=				int(os.environ["""SM_NUM_GPUS"""]			)
 UpperCAmelCase__ 						=				json.loads(os.environ["""SM_HOSTS"""]			)
 UpperCAmelCase__ 						=				len(_SCREAMING_SNAKE_CASE			)
 UpperCAmelCase__ 						=				os.environ["""SM_CURRENT_HOST"""]
 UpperCAmelCase__ 						=				hosts.index(_SCREAMING_SNAKE_CASE			)
 UpperCAmelCase__ 						=				"""INFO"""

 if num_nodes > 1:
  UpperCAmelCase__ 						=				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__ 						=				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(_SCREAMING_SNAKE_CASE       ,	shell=_SCREAMING_SNAKE_CASE			)
 except Exception as e:
  logger.info(_SCREAMING_SNAKE_CASE			)


if __name__ == "__main__":
 main()



