

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 _UpperCamelCase				:
			'''simple docstring'''







			lowerCamelCase__							     =42
			lowerCamelCase__							     =None
			@staticmethod
			def 				__UpperCamelCase			(      )				->							Any:

				"""simple docstring"""

				raise NotImplementedError
			def 				__UpperCamelCase			(      self				:			str   ,   a				:			Optional[Any]   ,   a				:			int   ,   a				:			str   ,   **a				:			int						)				->							Union[str, Any]:

				"""simple docstring"""

				raise NotImplementedError
			def 				__UpperCamelCase			(      self				:			Any   ,   a				:			List[Any]						)				->							Union[str, Any]:

				"""simple docstring"""

				raise NotImplementedError
			def 				__UpperCamelCase			(      self				:			Tuple						)				->							Union[str, Any]:

				"""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				:			str						)				->							Optional[Any]:

				"""simple docstring"""

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






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			lowerCamelCase__							     ='optuna'
			@staticmethod
			def 				__UpperCamelCase			(      )				->							Tuple:

				"""simple docstring"""

				return is_optuna_available()
			def 				__UpperCamelCase			(      self				:			List[str]   ,   a				:			Tuple   ,   a				:			int   ,   a				:			str   ,   **a				:			Optional[Any]						)				->							Union[str, Any]:

				"""simple docstring"""

				return run_hp_search_optuna(a   ,   a   ,   a   ,   **a						)






			def 				__UpperCamelCase			(      self				:			Optional[int]   ,   a				:			Optional[Any]						)				->							Tuple:

				"""simple docstring"""

				return default_hp_space_optuna(a						)






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			lowerCamelCase__							     ='ray'
			lowerCamelCase__							     ='\'ray[tune]\''
			@staticmethod
			def 				__UpperCamelCase			(      )				->							List[Any]:

				"""simple docstring"""

				return is_ray_available()
			def 				__UpperCamelCase			(      self				:			Tuple   ,   a				:			str   ,   a				:			int   ,   a				:			str   ,   **a				:			str						)				->							Tuple:

				"""simple docstring"""

				return run_hp_search_ray(a   ,   a   ,   a   ,   **a						)






			def 				__UpperCamelCase			(      self				:			int   ,   a				:			Optional[int]						)				->							List[Any]:

				"""simple docstring"""

				return default_hp_space_ray(a						)






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			lowerCamelCase__							     ='sigopt'
			@staticmethod
			def 				__UpperCamelCase			(      )				->							int:

				"""simple docstring"""

				return is_sigopt_available()
			def 				__UpperCamelCase			(      self				:			List[Any]   ,   a				:			Any   ,   a				:			int   ,   a				:			str   ,   **a				:			int						)				->							Optional[int]:

				"""simple docstring"""

				return run_hp_search_sigopt(a   ,   a   ,   a   ,   **a						)






			def 				__UpperCamelCase			(      self				:			Optional[Any]   ,   a				:			Dict						)				->							str:

				"""simple docstring"""

				return default_hp_space_sigopt(a						)






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			lowerCamelCase__							     ='wandb'
			@staticmethod
			def 				__UpperCamelCase			(      )				->							Dict:

				"""simple docstring"""

				return is_wandb_available()
			def 				__UpperCamelCase			(      self				:			List[str]   ,   a				:			Optional[Any]   ,   a				:			int   ,   a				:			str   ,   **a				:			List[Any]						)				->							List[str]:

				"""simple docstring"""

				return run_hp_search_wandb(a   ,   a   ,   a   ,   **a						)






			def 				__UpperCamelCase			(      self				:			Tuple   ,   a				:			Optional[int]						)				->							int:

				"""simple docstring"""

				return default_hp_space_wandb(a						)

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

def 			lowerCamelCase__			(       ):
	SCREAMING_SNAKE_CASE :   int					  =							[backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
	if len(_a) > 0:
		SCREAMING_SNAKE_CASE :   Tuple					  =							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 ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE									=				logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE									=				{
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}

class  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				Union[str, Any]								=       "swinv2"

 __lowerCamelCase    :				int								=       {
     "num_attention_heads": "num_heads",
     "num_hidden_layers": "num_layers",
 }




 def __init__(						self      ,  _lowerCAmelCase=224      ,  _lowerCAmelCase=4      ,  _lowerCAmelCase=3      ,  _lowerCAmelCase=96      ,  _lowerCAmelCase=[2, 2, 6, 2]      ,  _lowerCAmelCase=[3, 6, 12, 24]      ,  _lowerCAmelCase=7      ,  _lowerCAmelCase=4.0      ,  _lowerCAmelCase=True      ,  _lowerCAmelCase=0.0      ,  _lowerCAmelCase=0.0      ,  _lowerCAmelCase=0.1      ,  _lowerCAmelCase="gelu"      ,  _lowerCAmelCase=False      ,  _lowerCAmelCase=0.02      ,  _lowerCAmelCase=1E-5      ,  _lowerCAmelCase=32      ,  **_lowerCAmelCase      ,  )     ->				Tuple:
     super().__init__(**_lowerCAmelCase		)

     _lowerCAmelCase						      =   image_size
     _lowerCAmelCase						      =   patch_size
     _lowerCAmelCase						      =   num_channels
     _lowerCAmelCase						      =   embed_dim
     _lowerCAmelCase						      =   depths
     _lowerCAmelCase						      =   len(_lowerCAmelCase		)
     _lowerCAmelCase						      =   num_heads
     _lowerCAmelCase						      =   window_size
     _lowerCAmelCase						      =   mlp_ratio
     _lowerCAmelCase						      =   qkv_bias
     _lowerCAmelCase						      =   hidden_dropout_prob
     _lowerCAmelCase						      =   attention_probs_dropout_prob
     _lowerCAmelCase						      =   drop_path_rate
     _lowerCAmelCase						      =   hidden_act
     _lowerCAmelCase						      =   use_absolute_embeddings
     _lowerCAmelCase						      =   layer_norm_eps
     _lowerCAmelCase						      =   initializer_range
     _lowerCAmelCase						      =   encoder_stride
     # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
     # this indicates the channel dimension after the last stage of the model
     _lowerCAmelCase						      =   int(embed_dim * 2 ** (len(_lowerCAmelCase		) - 1)		)
     _lowerCAmelCase						      =   (0, 0, 0, 0)


