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


UpperCAmelCase							=       logging.getLogger(__name__)






def 					SCREAMING_SNAKE_CASE_			(		):
      snake_case_     :			str       =       ArgumentParser()
      snake_case_  ,snake_case_     :			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_			(		):
      snake_case_     :			str       =       parse_args()
      snake_case_     :			Union[str, Any]       =       8_8_8_8
      snake_case_     :			Dict       =       int(os.environ["SM_NUM_GPUS"]     )
      snake_case_     :			Tuple       =       json.loads(os.environ["SM_HOSTS"]     )
      snake_case_     :			Optional[Any]       =       len(lowerCAmelCase_     )
      snake_case_     :			int       =       os.environ["SM_CURRENT_HOST"]
      snake_case_     :			Optional[int]       =       hosts.index(lowerCAmelCase_     )
      snake_case_     :			int       =       "INFO"

      if num_nodes > 1:
            snake_case_     :			Optional[int]       =       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:
            snake_case_     :			Union[str, Any]       =       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(lowerCAmelCase_ ,	shell=lowerCAmelCase_     )
      except Exception as e:
            logger.info(lowerCAmelCase_     )


if __name__ == "__main__":
     main()




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase							=       {
    "configuration_nystromformer": ["NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "NystromformerConfig"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase							=       [
         "NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
         "NystromformerForMaskedLM",
         "NystromformerForMultipleChoice",
         "NystromformerForQuestionAnswering",
         "NystromformerForSequenceClassification",
         "NystromformerForTokenClassification",
         "NystromformerLayer",
         "NystromformerModel",
         "NystromformerPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_nystromformer import (
              NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              NystromformerForMaskedLM,
              NystromformerForMultipleChoice,
              NystromformerForQuestionAnswering,
              NystromformerForSequenceClassification,
              NystromformerForTokenClassification,
              NystromformerLayer,
              NystromformerModel,
              NystromformerPreTrainedModel,
          )


else:
     import sys

     UpperCAmelCase							=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



