


import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp







def   lowerCamelCase(				):
				_SCREAMING_SNAKE_CASE     					=ArgumentParser(
				    description=(
				        '''PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes'''
				    ))

				# Optional arguments for the launch helper
				parser.add_argument('''--num_cores'''		,type=a__		,default=1		,help='''Number of TPU cores to use (1 or 8).''')

				# positional
				parser.add_argument(
				    '''training_script'''		,type=a__		,help=(
				        '''The full path to the single TPU training '''
				        '''program/script to be launched in parallel, '''
				        '''followed by all the arguments for the '''
				        '''training script'''
				    )		,)

				# rest from the training program
				parser.add_argument('''training_script_args'''		,nargs=a__)

				return parser.parse_args()







def   lowerCamelCase(				):
				_SCREAMING_SNAKE_CASE     					=parse_args()

				# Import training_script as a module.
				_SCREAMING_SNAKE_CASE     					=Path(args.training_script)
				sys.path.append(str(script_fpath.parent.resolve()))
				_SCREAMING_SNAKE_CASE     					=script_fpath.stem
				_SCREAMING_SNAKE_CASE     					=importlib.import_module(a__)

				# Patch sys.argv
				_SCREAMING_SNAKE_CASE     					=[args.training_script] + args.training_script_args + ['''--tpu_num_cores''', str(args.num_cores)]

				xmp.spawn(mod._mp_fn		,args=()		,nprocs=args.num_cores)


if __name__ == "__main__":
							main()



import math







def   lowerCamelCase(				a__):
				_SCREAMING_SNAKE_CASE     					=math.log(2		,10) * number
				_SCREAMING_SNAKE_CASE     					=round((log_number - int(a__))		,15)

				return difference







def   lowerCamelCase(				a__ = 67_8910):
				_SCREAMING_SNAKE_CASE     					=90
				_SCREAMING_SNAKE_CASE     					=0

				_SCREAMING_SNAKE_CASE     					=math.log(1.23		,10)
				_SCREAMING_SNAKE_CASE     					=math.log(1.24		,10)
				_SCREAMING_SNAKE_CASE     					=0

				while position < number:
								_SCREAMING_SNAKE_CASE     					=log_difference(a__)

								if difference >= upper_limit:
												power_iterator += 93

								elif difference < lower_limit:
												power_iterator += 196

								else:
												_SCREAMING_SNAKE_CASE     					=power_iterator
												power_iterator += 196
												position += 1

				return previous_power


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							print(f"""{solution() = }""")