

'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__SCREAMING_SNAKE_CASE     =						{
    'configuration_funnel': ['FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FunnelConfig'],
    'convert_funnel_original_tf_checkpoint_to_pytorch': [],
    'tokenization_funnel': ['FunnelTokenizer'],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __SCREAMING_SNAKE_CASE     =						['FunnelTokenizerFast']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __SCREAMING_SNAKE_CASE     =						[
     'FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST',
     'FunnelBaseModel',
     'FunnelForMaskedLM',
     'FunnelForMultipleChoice',
     'FunnelForPreTraining',
     'FunnelForQuestionAnswering',
     'FunnelForSequenceClassification',
     'FunnelForTokenClassification',
     'FunnelModel',
     'FunnelPreTrainedModel',
     'load_tf_weights_in_funnel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __SCREAMING_SNAKE_CASE     =						[
     'TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFFunnelBaseModel',
     'TFFunnelForMaskedLM',
     'TFFunnelForMultipleChoice',
     'TFFunnelForPreTraining',
     'TFFunnelForQuestionAnswering',
     'TFFunnelForSequenceClassification',
     'TFFunnelForTokenClassification',
     'TFFunnelModel',
     'TFFunnelPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig
 from .tokenization_funnel import FunnelTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_funnel_fast import FunnelTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_funnel import (
      FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
      FunnelBaseModel,
      FunnelForMaskedLM,
      FunnelForMultipleChoice,
      FunnelForPreTraining,
      FunnelForQuestionAnswering,
      FunnelForSequenceClassification,
      FunnelForTokenClassification,
      FunnelModel,
      FunnelPreTrainedModel,
      load_tf_weights_in_funnel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_funnel import (
      TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFFunnelBaseModel,
      TFFunnelForMaskedLM,
      TFFunnelForMultipleChoice,
      TFFunnelForPreTraining,
      TFFunnelForQuestionAnswering,
      TFFunnelForSequenceClassification,
      TFFunnelForTokenClassification,
      TFFunnelModel,
      TFFunnelPreTrainedModel,
  )

else:
 import sys

 __SCREAMING_SNAKE_CASE     =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


import math





def      lowerCamelCase_					(							lowerCamelCase__      ,					lowerCamelCase__       ):
				if 0 not in (x, y):
								# We use the relation x^y = y*log10(x), where 10 is the base.
								return y * math.logaa(lowerCamelCase__       )
				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''')


