

from .integrations import (
    is_optuna_available,
    is_ray_available,
    is_sigopt_available,
    is_wandb_available,
    run_hp_search_optuna,
    run_hp_search_ray,
    run_hp_search_sigopt,
    run_hp_search_wandb,
)
from .trainer_utils import (
    HPSearchBackend,
    default_hp_space_optuna,
    default_hp_space_ray,
    default_hp_space_sigopt,
    default_hp_space_wandb,
)
from .utils import logging


lowercase_									=   logging.get_logger(__name__)





class  __lowerCAmelCase     :
  _a									=  42
  _a									=  None




  @staticmethod
  def   A__     (				)  -> Optional[Any]:
        '''simple docstring'''






        raise NotImplementedError




  def   A__     (				self							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)  -> Any:
        '''simple docstring'''






        raise NotImplementedError




  def   A__     (				self							,   lowerCAmelCase					)  -> Optional[int]:
        '''simple docstring'''






        raise NotImplementedError




  def   A__     (				self					)  -> Dict:
        '''simple docstring'''






        if not self.is_available():
              raise RuntimeError(
                  F'''You picked the {self.name} backend, but it is not installed. Run {self.pip_install()}.'''					)




  @classmethod
  def   A__     (				cls					)  -> List[str]:
        '''simple docstring'''






        return F'''`pip install {cls.pip_package or cls.name}`'''





class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE							):
  _a									=  'optuna'




  @staticmethod
  def   A__     (				)  -> str:
        '''simple docstring'''






        return is_optuna_available()




  def   A__     (				self							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)  -> List[Any]:
        '''simple docstring'''






        return run_hp_search_optuna(lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)




  def   A__     (				self							,   lowerCAmelCase					)  -> Optional[int]:
        '''simple docstring'''






        return default_hp_space_optuna(lowerCAmelCase					)





class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE							):
  _a									=  'ray'
  _a									=  '\'ray[tune]\''




  @staticmethod
  def   A__     (				)  -> List[Any]:
        '''simple docstring'''






        return is_ray_available()




  def   A__     (				self							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)  -> Tuple:
        '''simple docstring'''






        return run_hp_search_ray(lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)




  def   A__     (				self							,   lowerCAmelCase					)  -> List[str]:
        '''simple docstring'''






        return default_hp_space_ray(lowerCAmelCase					)





class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE							):
  _a									=  'sigopt'




  @staticmethod
  def   A__     (				)  -> Any:
        '''simple docstring'''






        return is_sigopt_available()




  def   A__     (				self							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)  -> Any:
        '''simple docstring'''






        return run_hp_search_sigopt(lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)




  def   A__     (				self							,   lowerCAmelCase					)  -> Optional[Any]:
        '''simple docstring'''






        return default_hp_space_sigopt(lowerCAmelCase					)





class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE							):
  _a									=  'wandb'




  @staticmethod
  def   A__     (				)  -> str:
        '''simple docstring'''






        return is_wandb_available()




  def   A__     (				self							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)  -> List[str]:
        '''simple docstring'''






        return run_hp_search_wandb(lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   **lowerCAmelCase					)




  def   A__     (				self							,   lowerCAmelCase					)  -> str:
        '''simple docstring'''






        return default_hp_space_wandb(lowerCAmelCase					)
lowercase_									=   {
    HPSearchBackend(backend.name): backend for backend in [OptunaBackend, RayTuneBackend, SigOptBackend, WandbBackend]
}
def      a      (			)    ->      List[str]:





      """simple docstring"""



      _lowercase	       =[backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
      if len(__A     ) > 0:
            _lowercase	       =available_backends[0].name
            if len(__A     ) > 1:
                  logger.info(
                      F'''{len(__A     )} hyperparameter search backends available. Using {name} as the default.'''     )
            return name
      raise RuntimeError(
          'No hyperparameter search backend available.\n'
          + '\n'.join(
              F''' - To install {backend.name} run {backend.pip_install()}'''
              for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values()     )     )







'''simple docstring'''





from __future__ import annotations

import math




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     _a      =  u
     for i in range(1  ,	__A):
          _a      =  temp * (u - i)
     return temp




def lowerCAmelCase  ():



     """simple docstring"""



     _a      =  int(input('''enter the numbers of values: '''))
     _a      =  []
     for _ in range(__A):
          y.append([])
     for i in range(__A):
          for j in range(__A):
               y[i].append(__A)
               _a      =  0

     print('''enter the values of parameters in a list: ''')
     _a      =  list(map(__A  ,	input().split()))

     print('''enter the values of corresponding parameters: ''')
     for i in range(__A):
          _a      =  float(input())

     _a      =  int(input('''enter the value to interpolate: '''))
     _a      =  (value - x[0]) / (x[1] - x[0])

     # for calculating forward difference table

     for i in range(1  ,	__A):
          for j in range(n - i):
               _a      =  y[j + 1][i - 1] - y[j][i - 1]

     _a      =  y[0][0]
     for i in range(1  ,	__A):
          summ += (ucal(__A  ,	__A) * y[0][i]) / math.factorial(__A)

     print(F'''the value at {value} is {summ}''')


if __name__ == "__main__":
  main()



