






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_							=			logging.get_logger(__name__)


class    lowercase__   :
	a_   			=42
	a_   			=None

	@staticmethod
	def 						UpperCAmelCase     (							)->    Dict:







							'''simple docstring'''





							raise NotImplementedError

	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase						,			__UpperCAmelCase						,			__UpperCAmelCase						,			**__UpperCAmelCase				)->    Union[str, Any]:







							'''simple docstring'''





							raise NotImplementedError

	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase				)->    Dict:







							'''simple docstring'''





							raise NotImplementedError

	def 						UpperCAmelCase     (							self				)->    List[str]:







							'''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 						UpperCAmelCase     (							cls				)->    Dict:







							'''simple docstring'''





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





class    lowercase__   (	snake_case_		):
	a_   			='''optuna'''

	@staticmethod
	def 						UpperCAmelCase     (							)->    List[Any]:







							'''simple docstring'''





							return is_optuna_available()

	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase						,			__UpperCAmelCase						,			__UpperCAmelCase						,			**__UpperCAmelCase				)->    int:







							'''simple docstring'''





							return run_hp_search_optuna(UpperCAmelCase__						,			UpperCAmelCase__						,			UpperCAmelCase__						,			**UpperCAmelCase__				)


	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase				)->    Optional[Any]:







							'''simple docstring'''





							return default_hp_space_optuna(UpperCAmelCase__				)





class    lowercase__   (	snake_case_		):
	a_   			='''ray'''
	a_   			='''\'ray[tune]\''''

	@staticmethod
	def 						UpperCAmelCase     (							)->    List[Any]:







							'''simple docstring'''





							return is_ray_available()

	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase						,			__UpperCAmelCase						,			__UpperCAmelCase						,			**__UpperCAmelCase				)->    List[str]:







							'''simple docstring'''





							return run_hp_search_ray(UpperCAmelCase__						,			UpperCAmelCase__						,			UpperCAmelCase__						,			**UpperCAmelCase__				)


	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase				)->    Optional[int]:







							'''simple docstring'''





							return default_hp_space_ray(UpperCAmelCase__				)





class    lowercase__   (	snake_case_		):
	a_   			='''sigopt'''

	@staticmethod
	def 						UpperCAmelCase     (							)->    str:







							'''simple docstring'''





							return is_sigopt_available()

	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase						,			__UpperCAmelCase						,			__UpperCAmelCase						,			**__UpperCAmelCase				)->    List[Any]:







							'''simple docstring'''





							return run_hp_search_sigopt(UpperCAmelCase__						,			UpperCAmelCase__						,			UpperCAmelCase__						,			**UpperCAmelCase__				)


	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase				)->    Union[str, Any]:







							'''simple docstring'''





							return default_hp_space_sigopt(UpperCAmelCase__				)





class    lowercase__   (	snake_case_		):
	a_   			='''wandb'''

	@staticmethod
	def 						UpperCAmelCase     (							)->    Optional[Any]:







							'''simple docstring'''





							return is_wandb_available()

	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase						,			__UpperCAmelCase						,			__UpperCAmelCase						,			**__UpperCAmelCase				)->    Any:







							'''simple docstring'''





							return run_hp_search_wandb(UpperCAmelCase__						,			UpperCAmelCase__						,			UpperCAmelCase__						,			**UpperCAmelCase__				)


	def 						UpperCAmelCase     (							self						,			__UpperCAmelCase				)->    str:







							'''simple docstring'''





							return default_hp_space_wandb(UpperCAmelCase__				)





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


def 				_a     (   )       ->      Optional[int]:
						"""simple docstring"""







						lowerCAmelCase__       					=  [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
						if len(UpperCamelCase__      ) > 0:
												lowerCAmelCase__       					=  available_backends[0].name
												if len(UpperCamelCase__      ) > 1:
																		logger.info(
																		    F"{len(UpperCamelCase__      )} 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_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


_snake_case          =   {
    'configuration_perceiver': ['PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PerceiverConfig', 'PerceiverOnnxConfig'],
    'tokenization_perceiver': ['PerceiverTokenizer'],
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _snake_case          =   ['PerceiverFeatureExtractor']
 _snake_case          =   ['PerceiverImageProcessor']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _snake_case          =   [
     'PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'PerceiverForImageClassificationConvProcessing',
     'PerceiverForImageClassificationFourier',
     'PerceiverForImageClassificationLearned',
     'PerceiverForMaskedLM',
     'PerceiverForMultimodalAutoencoding',
     'PerceiverForOpticalFlow',
     'PerceiverForSequenceClassification',
     'PerceiverLayer',
     'PerceiverModel',
     'PerceiverPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_perceiver import PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP, PerceiverConfig, PerceiverOnnxConfig
 from .tokenization_perceiver import PerceiverTokenizer

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_perceiver import PerceiverFeatureExtractor
  from .image_processing_perceiver import PerceiverImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_perceiver import (
      PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST,
      PerceiverForImageClassificationConvProcessing,
      PerceiverForImageClassificationFourier,
      PerceiverForImageClassificationLearned,
      PerceiverForMaskedLM,
      PerceiverForMultimodalAutoencoding,
      PerceiverForOpticalFlow,
      PerceiverForSequenceClassification,
      PerceiverLayer,
      PerceiverModel,
      PerceiverPreTrainedModel,
  )

else:
 import sys

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

