'''simple docstring'''
import math







def  _UpperCamelCase (     _a	:	Tuple				,     _a	:	List[str]			):




				"""simple docstring"""



				if 0 not in (x, y):
								# We use the relation x^y = y*log10(x), where 10 is the base.
								return y * math.logaa(_a			)
				else:
								if x == 0:  # 0 raised to any number is 0
												return 0
								elif y == 0:
												return 1  # any number raised to 0 is 1
				raise AssertionError('This should never happen'			)


if __name__ == "__main__":  # Main function
		# Read two numbers from input and typecast them to int using map function.
		# Here x is the base and y is the power.
		a=  '''Enter the base and the power separated by a comma: '''
		a,			a=  map(int, input(prompt).split(''','''))
		a,			a=  map(int, input(prompt).split(''','''))

		# We find the log of each number, using the function res(), which takes two
		# arguments.
		a=  res(xa, ya)
		a=  res(xa, ya)

		# We check for the largest number
		if resa > resa:
				print('''Largest number is''', xa, '''^''', ya)
		elif resa > resa:
				print('''Largest number is''', xa, '''^''', ya)
		else:
				print('''Both are equal''')




'''simple docstring'''
a=  '''0.21.0'''

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
  from .utils import rich



