



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 					__lowerCAmelCase :
				__lowerCamelCase =				42
				__lowerCamelCase =				None




				@staticmethod
				def 							snake_case   (							):



									"""simple docstring"""





									raise NotImplementedError




				def 							snake_case   (							self						,				_snake_case						,				_snake_case						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





									raise NotImplementedError




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





									raise NotImplementedError




				def 							snake_case   (							self		):



									"""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 							snake_case   (							cls		):



									"""simple docstring"""





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





class 					__lowerCAmelCase (     lowerCamelCase__       ):
				__lowerCamelCase =				'optuna'




				@staticmethod
				def 							snake_case   (							):



									"""simple docstring"""





									return is_optuna_available()




				def 							snake_case   (							self						,				_snake_case						,				_snake_case						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





									return run_hp_search_optuna(SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				**SCREAMING_SNAKE_CASE_		)




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





									return default_hp_space_optuna(SCREAMING_SNAKE_CASE_		)





class 					__lowerCAmelCase (     lowerCamelCase__       ):
				__lowerCamelCase =				'ray'
				__lowerCamelCase =				'\'ray[tune]\''




				@staticmethod
				def 							snake_case   (							):



									"""simple docstring"""





									return is_ray_available()




				def 							snake_case   (							self						,				_snake_case						,				_snake_case						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





									return run_hp_search_ray(SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				**SCREAMING_SNAKE_CASE_		)




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





									return default_hp_space_ray(SCREAMING_SNAKE_CASE_		)





class 					__lowerCAmelCase (     lowerCamelCase__       ):
				__lowerCamelCase =				'sigopt'




				@staticmethod
				def 							snake_case   (							):



									"""simple docstring"""





									return is_sigopt_available()




				def 							snake_case   (							self						,				_snake_case						,				_snake_case						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





									return run_hp_search_sigopt(SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				**SCREAMING_SNAKE_CASE_		)




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





									return default_hp_space_sigopt(SCREAMING_SNAKE_CASE_		)





class 					__lowerCAmelCase (     lowerCamelCase__       ):
				__lowerCamelCase =				'wandb'




				@staticmethod
				def 							snake_case   (							):



									"""simple docstring"""





									return is_wandb_available()




				def 							snake_case   (							self						,				_snake_case						,				_snake_case						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





									return run_hp_search_wandb(SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				SCREAMING_SNAKE_CASE_						,				**SCREAMING_SNAKE_CASE_		)




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





									return default_hp_space_wandb(SCREAMING_SNAKE_CASE_		)

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


def 		_UpperCAmelCase				(      ):





					"""simple docstring"""

					_lowerCAmelCase						=    [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
					if len(snake_case__			) > 0:
										_lowerCAmelCase						=    available_backends[0].name
										if len(snake_case__			) > 1:
															logger.info(
															    F'{len(snake_case__			)} 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()			)			)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


__a  			=					{
    'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TrOCRConfig'],
    'processing_trocr': ['TrOCRProcessor'],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a  			=					[
						    'TROCR_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TrOCRForCausalLM',
						    'TrOCRPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
						from .processing_trocr import TrOCRProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
						import sys

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




