



"""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_     =	logging.get_logger(__name__)




class  _snake_case		:







				"""simple docstring"""






				a			=						42
				a			=						None





				@staticmethod
				def 		_lowerCAmelCase		(      ):



											"""simple docstring"""







											raise NotImplementedError





				def 		_lowerCAmelCase		(      self							:							Dict      ,    _A							:							Optional[Any]      ,    _A							:							Union[str, Any]      ,    _A							:							Optional[Any]      ,    **_A							:							Dict):



											"""simple docstring"""







											raise NotImplementedError





				def 		_lowerCAmelCase		(      self							:							List[Any]      ,    _A							:							Any):



											"""simple docstring"""







											raise NotImplementedError





				def 		_lowerCAmelCase		(      self							:							Optional[int]):



											"""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 		_lowerCAmelCase		(      cls							:							Tuple):



											"""simple docstring"""







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




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						"optuna"





				@staticmethod
				def 		_lowerCAmelCase		(      ):



											"""simple docstring"""







											return is_optuna_available()





				def 		_lowerCAmelCase		(      self							:							List[Any]      ,    _A							:							Any      ,    _A							:							str      ,    _A							:							Tuple      ,    **_A							:							List[Any]):



											"""simple docstring"""







											return run_hp_search_optuna(_lowerCAmelCase      ,    _lowerCAmelCase      ,    _lowerCAmelCase      ,    **_lowerCAmelCase)





				def 		_lowerCAmelCase		(      self							:							Optional[Any]      ,    _A							:							int):



											"""simple docstring"""







											return default_hp_space_optuna(_lowerCAmelCase)




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						"ray"
				a			=						"\'ray[tune]\'"





				@staticmethod
				def 		_lowerCAmelCase		(      ):



											"""simple docstring"""







											return is_ray_available()





				def 		_lowerCAmelCase		(      self							:							List[str]      ,    _A							:							List[str]      ,    _A							:							Optional[Any]      ,    _A							:							List[str]      ,    **_A							:							List[Any]):



											"""simple docstring"""







											return run_hp_search_ray(_lowerCAmelCase      ,    _lowerCAmelCase      ,    _lowerCAmelCase      ,    **_lowerCAmelCase)





				def 		_lowerCAmelCase		(      self							:							int      ,    _A							:							Optional[int]):



											"""simple docstring"""







											return default_hp_space_ray(_lowerCAmelCase)




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						"sigopt"





				@staticmethod
				def 		_lowerCAmelCase		(      ):



											"""simple docstring"""







											return is_sigopt_available()





				def 		_lowerCAmelCase		(      self							:							Optional[Any]      ,    _A							:							Union[str, Any]      ,    _A							:							str      ,    _A							:							List[Any]      ,    **_A							:							Optional[int]):



											"""simple docstring"""







											return run_hp_search_sigopt(_lowerCAmelCase      ,    _lowerCAmelCase      ,    _lowerCAmelCase      ,    **_lowerCAmelCase)





				def 		_lowerCAmelCase		(      self							:							Tuple      ,    _A							:							Optional[int]):



											"""simple docstring"""







											return default_hp_space_sigopt(_lowerCAmelCase)




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						"wandb"





				@staticmethod
				def 		_lowerCAmelCase		(      ):



											"""simple docstring"""







											return is_wandb_available()





				def 		_lowerCAmelCase		(      self							:							List[Any]      ,    _A							:							str      ,    _A							:							Optional[int]      ,    _A							:							Union[str, Any]      ,    **_A							:							Optional[Any]):



											"""simple docstring"""







											return run_hp_search_wandb(_lowerCAmelCase      ,    _lowerCAmelCase      ,    _lowerCAmelCase      ,    **_lowerCAmelCase)





				def 		_lowerCAmelCase		(      self							:							Optional[Any]      ,    _A							:							List[str]):



											"""simple docstring"""







											return default_hp_space_wandb(_lowerCAmelCase)


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



def      lowerCamelCase_()->    Dict:
							_SCREAMING_SNAKE_CASE		:						Any			  =    [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
							if len(__lowerCAmelCase  ) > 0:
														_SCREAMING_SNAKE_CASE		:						Tuple			  =    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"""





import unittest

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device


if is_torch_available():
			import torch

			from transformers import AutoModelForImageClassification

if is_vision_available():
			from transformers import AutoImageProcessor




@require_torch
@require_vision
class  _snake_case		(    unittest.TestCase ):







				"""simple docstring"""






				@slow
				def 		_lowerCAmelCase		(      self							:							str):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Any			  =    AutoImageProcessor.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip""")
											_SCREAMING_SNAKE_CASE		:						str			  =    AutoModelForImageClassification.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip""")
											model.to(_A)

											from datasets import load_dataset

											_SCREAMING_SNAKE_CASE		:						Any			  =    load_dataset("""nielsr/rvlcdip-demo""")

											_SCREAMING_SNAKE_CASE		:						Any			  =    dataset["""train"""][0]["""image"""].convert("""RGB""")

											_SCREAMING_SNAKE_CASE		:						str			  =    image_processor(_A      ,    return_tensors="""pt""").to(_A)

											# forward pass
											with torch.no_grad():
																		_SCREAMING_SNAKE_CASE		:						Any			  =    model(**_A)
																		_SCREAMING_SNAKE_CASE		:						List[Any]			  =    outputs.logits

											_SCREAMING_SNAKE_CASE		:						List[str]			  =    torch.Size((1, 1_6))
											self.assertEqual(logits.shape      ,    _A)

											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    torch.tensor(
											    [-0.4_158, -0.4_092, -0.4_347]      ,    device=_A      ,    dtype=torch.float      ,    )
											self.assertTrue(torch.allclose(logits[0, :3]      ,    _A      ,    atol=1e-4))


