






'''simple docstring'''

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


lowerCAmelCase_ : str						  =      logging.get_logger(__name__)





class 							lowercase						:
   lowerCamelCase_    					=4_2
   lowerCamelCase_    					=None


   @staticmethod
   def __UpperCAmelCase       (   )      ->					Union[str, Any]:
         raise NotImplementedError


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	List[Any]   ,		__lowerCAmelCase				:	int   ,		__lowerCAmelCase				:	str   ,		**__lowerCAmelCase				:	Any)      ->					str:
         raise NotImplementedError


   def __UpperCAmelCase       (   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	int)      ->					int:
         raise NotImplementedError


   def __UpperCAmelCase       (   self				:	int)      ->					Any:
         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 __UpperCAmelCase       (   cls				:	int)      ->					List[str]:
         return F'`pip install {cls.pip_package or cls.name}`'





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='optuna'


   @staticmethod
   def __UpperCAmelCase       (   )      ->					Any:
         return is_optuna_available()


   def __UpperCAmelCase       (   self				:	Optional[Any]   ,		__lowerCAmelCase				:	Any   ,		__lowerCAmelCase				:	int   ,		__lowerCAmelCase				:	str   ,		**__lowerCAmelCase				:	int)      ->					Any:
         return run_hp_search_optuna(__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	str   ,		__lowerCAmelCase				:	Tuple)      ->					Tuple:
         return default_hp_space_optuna(__lowerCAmelCase)





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='ray'
   lowerCamelCase_    					='\'ray[tune]\''


   @staticmethod
   def __UpperCAmelCase       (   )      ->					str:
         return is_ray_available()


   def __UpperCAmelCase       (   self				:	Optional[int]   ,		__lowerCAmelCase				:	List[str]   ,		__lowerCAmelCase				:	int   ,		__lowerCAmelCase				:	str   ,		**__lowerCAmelCase				:	str)      ->					Union[str, Any]:
         return run_hp_search_ray(__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	str)      ->					Union[str, Any]:
         return default_hp_space_ray(__lowerCAmelCase)





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='sigopt'


   @staticmethod
   def __UpperCAmelCase       (   )      ->					Union[str, Any]:
         return is_sigopt_available()


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	int   ,		__lowerCAmelCase				:	int   ,		__lowerCAmelCase				:	str   ,		**__lowerCAmelCase				:	List[str])      ->					int:
         return run_hp_search_sigopt(__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	int)      ->					Tuple:
         return default_hp_space_sigopt(__lowerCAmelCase)





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='wandb'


   @staticmethod
   def __UpperCAmelCase       (   )      ->					Optional[Any]:
         return is_wandb_available()


   def __UpperCAmelCase       (   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	Optional[int]   ,		__lowerCAmelCase				:	int   ,		__lowerCAmelCase				:	str   ,		**__lowerCAmelCase				:	Optional[int])      ->					List[str]:
         return run_hp_search_wandb(__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	List[str]   ,		__lowerCAmelCase				:	Tuple)      ->					Tuple:
         return default_hp_space_wandb(__lowerCAmelCase)




lowerCAmelCase_ : Tuple						  =      {
    HPSearchBackend(backend.name): backend for backend in [OptunaBackend, RayTuneBackend, SigOptBackend, WandbBackend]
}


def __a (	)	->							str:
      '''simple docstring'''


      lowercase_     =      [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
      if len(__lowerCamelCase				) > 0:
            lowercase_     =      available_backends[0].name
            if len(__lowerCamelCase				) > 1:
                  logger.info(
                      f'{len(__lowerCamelCase				)} 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 typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream





class 							lowercase						(						__lowerCamelCase ):


   def __init__(   self				:	str   ,		__lowerCAmelCase				:	Callable   ,		__lowerCAmelCase				:	Optional[Features] = None   ,		__lowerCAmelCase				:	str = None   ,		__lowerCAmelCase				:	bool = False   ,		__lowerCAmelCase				:	bool = False   ,		__lowerCAmelCase				:	Optional[dict] = None   ,		__lowerCAmelCase				:	Optional[int] = None   ,		**__lowerCAmelCase				:	Union[str, Any]   ,		)      ->					List[Any]:
         super().__init__(
             features=__lowerCAmelCase   ,		cache_dir=__lowerCAmelCase   ,		keep_in_memory=__lowerCAmelCase   ,		streaming=__lowerCAmelCase   ,		num_proc=__lowerCAmelCase   ,		**__lowerCAmelCase   ,		)
         lowercase_     =      Generator(
             cache_dir=__lowerCAmelCase   ,		features=__lowerCAmelCase   ,		generator=__lowerCAmelCase   ,		gen_kwargs=__lowerCAmelCase   ,		**__lowerCAmelCase   ,		)


   def __UpperCAmelCase       (   self				:	Optional[int])      ->					List[str]:
         # Build iterable dataset
         if self.streaming:
               lowercase_     =      self.builder.as_streaming_dataset(split="train")
         # Build regular (map-style) dataset
         else:
               lowercase_     =      None
               lowercase_     =      None
               lowercase_     =      None
               lowercase_     =      None

               self.builder.download_and_prepare(
                   download_config=__lowerCAmelCase   ,		download_mode=__lowerCAmelCase   ,		verification_mode=__lowerCAmelCase   ,		base_path=__lowerCAmelCase   ,		num_proc=self.num_proc   ,		)
               lowercase_     =      self.builder.as_dataset(
                   split="train"   ,		verification_mode=__lowerCAmelCase   ,		in_memory=self.keep_in_memory)
         return dataset






