




"""simple docstring"""




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


__A       :						Optional[int]												=			logging.getLogger(__name__)
def     A_	(						):







    '''simple docstring'''
    UpperCamelCase :      Union[str, Any]      				=							ArgumentParser()
    UpperCamelCase				,							UpperCamelCase :      Dict      				=							parser.parse_known_args()
    for arg in unknown:
        if arg.startswith(("""-""", """--""")			):
            parser.add_argument(arg.split("""="""			)[0]			)

    return parser.parse_args()
def     A_	(						):







    '''simple docstring'''
    UpperCamelCase :      List[Any]      				=							parse_args()
    UpperCamelCase :      Any      				=							8_8_8_8
    UpperCamelCase :      Optional[int]      				=							int(os.environ["""SM_NUM_GPUS"""]			)
    UpperCamelCase :      int      				=							json.loads(os.environ["""SM_HOSTS"""]			)
    UpperCamelCase :      Optional[Any]      				=							len(snake_case_			)
    UpperCamelCase :      Optional[Any]      				=							os.environ["""SM_CURRENT_HOST"""]
    UpperCamelCase :      int      				=							hosts.index(snake_case_			)
    UpperCamelCase :      int      				=							"""INFO"""

    if num_nodes > 1:
        UpperCamelCase :      Union[str, Any]      				=							f'python -m torch.distributed.launch \\n                --nnodes={num_nodes}  \\n                --node_rank={rank}  \\n                --nproc_per_node={num_gpus}  \\n                --master_addr={hosts[0]}  \\n                --master_port={port} \\n                ./run_glue.py \\n                {"".join(["nested fstring" for parameter,value in args.__dict__.items()]			)}'
    else:
        UpperCamelCase :      str      				=							f'python -m torch.distributed.launch \\n            --nproc_per_node={num_gpus}  \\n            ./run_glue.py \\n            {"".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()












"""simple docstring"""







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


lowerCAmelCase_		:			str				   =					logging.get_logger(__name__)

lowerCAmelCase_		:			Optional[int]				   =					{
    '''google/reformer-crime-and-punishment''': (
        '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json'''
    ),
    '''google/reformer-enwik8''': '''https://huggingface.co/google/reformer-enwik8/resolve/main/config.json''',
}





class      UpperCamelCase_       (				a_     ):
  _A				:    int =		'reformer'
  _A				:    Any =		['past_buckets_states']
  _A				:    Optional[Any] =		{}



  def __init__(					self       ,						snake_case__=64       ,						snake_case__=["local", "lsh", "local", "lsh", "local", "lsh"]       ,						snake_case__=1.0       ,						snake_case__=True       ,						snake_case__=[64, 64]       ,						snake_case__=[64, 1_92]       ,						snake_case__=0       ,						snake_case__=2       ,						snake_case__=5_12       ,						snake_case__=None       ,						snake_case__="relu"       ,						snake_case__=0.05       ,						snake_case__=2_56       ,						snake_case__=0.02       ,						snake_case__=False       ,						snake_case__=1e-12       ,						snake_case__=1       ,						snake_case__=0       ,						snake_case__=0.05       ,						snake_case__=64       ,						snake_case__=64       ,						snake_case__=0.0       ,						snake_case__=1       ,						snake_case__=0       ,						snake_case__=40_96       ,						snake_case__=12       ,						snake_case__=None       ,						snake_case__=1       ,						snake_case__=0       ,						snake_case__=3_20       ,						snake_case__=False       ,						snake_case__=True       ,						snake_case__=None       ,						**snake_case__       ,						)	->	List[Any]:



         """simple docstring"""





         UpperCAmelCase					=	hash_seed
         UpperCAmelCase					=	vocab_size
         UpperCAmelCase					=	attention_head_size
         UpperCAmelCase					=	hidden_size
         UpperCAmelCase					=	num_attention_heads
         UpperCAmelCase					=	num_hashes
         UpperCAmelCase					=	len(snake_case__ )
         UpperCAmelCase					=	tuple(snake_case__ ) if isinstance(snake_case__       ,						snake_case__ ) else num_buckets
         UpperCAmelCase					=	lsh_attn_chunk_length
         UpperCAmelCase					=	local_attn_chunk_length
         UpperCAmelCase					=	lsh_num_chunks_after
         UpperCAmelCase					=	lsh_num_chunks_before
         UpperCAmelCase					=	local_num_chunks_after
         UpperCAmelCase					=	local_num_chunks_before
         UpperCAmelCase					=	hidden_act
         UpperCAmelCase					=	feed_forward_size
         UpperCAmelCase					=	hidden_dropout_prob
         UpperCAmelCase					=	lsh_attention_probs_dropout_prob
         UpperCAmelCase					=	local_attention_probs_dropout_prob
         UpperCAmelCase					=	max_position_embeddings
         UpperCAmelCase					=	initializer_range
         UpperCAmelCase					=	layer_norm_eps
         UpperCAmelCase					=	axial_pos_embds
         UpperCAmelCase					=	tuple(snake_case__ )
         UpperCAmelCase					=	tuple(snake_case__ )
         UpperCAmelCase					=	axial_norm_std
         UpperCAmelCase					=	chunk_size_lm_head
         UpperCAmelCase					=	attn_layers
         UpperCAmelCase					=	use_cache
         UpperCAmelCase					=	classifier_dropout
         super().__init__(
             pad_token_id=snake_case__       ,						eos_token_id=snake_case__       ,						is_decoder=snake_case__       ,						tie_word_embeddings=snake_case__       ,						**snake_case__       ,						)
