"""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


_a   :	Union[str, Any] 					=     logging.get_logger(__name__)
class 		__A							:
     _UpperCamelCase							:    str
     _UpperCamelCase							:    str	      =	None






     @staticmethod
     def 					__A						(	):
       raise NotImplementedError






     def 					__A						(	self       ,  a__       ,  a__       ,  a__       ,  **a__						):
       raise NotImplementedError






     def 					__A						(	self       ,  a__						):
       raise NotImplementedError






     def 					__A						(	self						):
       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						):
       return F"`pip install {cls.pip_package or cls.name}`"







class 		__A							(				SCREAMING_SNAKE_CASE_	):
     _UpperCamelCase							:    List[Any]	      =	"optuna"






     @staticmethod
     def 					__A						(	):
       return is_optuna_available()






     def 					__A						(	self       ,  a__       ,  a__       ,  a__       ,  **a__						):
       return run_hp_search_optuna(a__       ,  a__       ,  a__       ,  **a__						)






     def 					__A						(	self       ,  a__						):
       return default_hp_space_optuna(a__						)







class 		__A							(				SCREAMING_SNAKE_CASE_	):
     _UpperCamelCase							:    Tuple	      =	"ray"
     _UpperCamelCase							:    Tuple	      =	"'ray[tune]'"






     @staticmethod
     def 					__A						(	):
       return is_ray_available()






     def 					__A						(	self       ,  a__       ,  a__       ,  a__       ,  **a__						):
       return run_hp_search_ray(a__       ,  a__       ,  a__       ,  **a__						)






     def 					__A						(	self       ,  a__						):
       return default_hp_space_ray(a__						)







class 		__A							(				SCREAMING_SNAKE_CASE_	):
     _UpperCamelCase							:    List[Any]	      =	"sigopt"






     @staticmethod
     def 					__A						(	):
       return is_sigopt_available()






     def 					__A						(	self       ,  a__       ,  a__       ,  a__       ,  **a__						):
       return run_hp_search_sigopt(a__       ,  a__       ,  a__       ,  **a__						)






     def 					__A						(	self       ,  a__						):
       return default_hp_space_sigopt(a__						)







class 		__A							(				SCREAMING_SNAKE_CASE_	):
     _UpperCamelCase							:    Optional[int]	      =	"wandb"






     @staticmethod
     def 					__A						(	):
       return is_wandb_available()






     def 					__A						(	self       ,  a__       ,  a__       ,  a__       ,  **a__						):
       return run_hp_search_wandb(a__       ,  a__       ,  a__       ,  **a__						)






     def 					__A						(	self       ,  a__						):
       return default_hp_space_wandb(a__						)







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





def 							SCREAMING_SNAKE_CASE  (    ) ->   str:
  _lowerCAmelCase		: str						    =  [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
  if len(_lowerCamelCase			) > 0:
    _lowerCAmelCase		: Optional[Any]						    =  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 TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_a   :	Tuple 					=     {'configuration_wavlm': ['WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'WavLMConfig']}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _a   :	str 					=     [
         'WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST',
         'WavLMForAudioFrameClassification',
         'WavLMForCTC',
         'WavLMForSequenceClassification',
         'WavLMForXVector',
         'WavLMModel',
         'WavLMPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_wavlm import (
              WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
              WavLMForAudioFrameClassification,
              WavLMForCTC,
              WavLMForSequenceClassification,
              WavLMForXVector,
              WavLMModel,
              WavLMPreTrainedModel,
          )

else:
     import sys

     _a   :	Any 					=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




