

"""simple docstring"""



import math





def  _snake_case     (    UpperCAmelCase_  :					Optional[int]					,   UpperCAmelCase_  :					List[str]			):






     if 0 not in (x, y):
          # We use the relation x^y = y*log10(x), where 10 is the base.
          return y * math.logaa(__UpperCamelCase			)
     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.
       SCREAMING_SNAKE_CASE_					:	Any							  =						'''Enter the base and the power separated by a comma: '''
       SCREAMING_SNAKE_CASE_					:	int							  =						map(int, input(prompt).split(','))
       SCREAMING_SNAKE_CASE_					:	Any							  =						map(int, input(prompt).split(','))

       # We find the log of each number, using the function res(), which takes two
       # arguments.
       SCREAMING_SNAKE_CASE_					:	Tuple							  =						res(xa, ya)
       SCREAMING_SNAKE_CASE_					:	List[Any]							  =						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"""



SCREAMING_SNAKE_CASE_					:	str							  =						'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






