






"""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	:	str				=      logging.get_logger(__name__)




class 			lowerCAmelCase__			:
   SCREAMING_SNAKE_CASE_    =42
   SCREAMING_SNAKE_CASE_    =None
   @staticmethod
   def       __a							(		):


        '''simple docstring'''
        raise NotImplementedError
   def       __a							(		self      :	Optional[Any]							,			snake_case__      :	Tuple							,			snake_case__      :	int							,			snake_case__      :	str							,			**snake_case__      :	Dict							):


        '''simple docstring'''
        raise NotImplementedError
   def       __a							(		self      :	Optional[int]							,			snake_case__      :	str							):


        '''simple docstring'''
        raise NotImplementedError
   def       __a							(		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       __a							(		cls      :	Union[str, Any]							):


        '''simple docstring'''
        return f'`pip install {cls.pip_package or cls.name}`'




class 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    ='''optuna'''
   @staticmethod
   def       __a							(		):


        '''simple docstring'''
        return is_optuna_available()
   def       __a							(		self      :	int							,			snake_case__      :	Optional[int]							,			snake_case__      :	int							,			snake_case__      :	str							,			**snake_case__      :	str							):


        '''simple docstring'''
        return run_hp_search_optuna(snake_case__							,			snake_case__							,			snake_case__							,			**snake_case__							)




   def       __a							(		self      :	int							,			snake_case__      :	str							):


        '''simple docstring'''
        return default_hp_space_optuna(snake_case__							)




class 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    ='''ray'''
   SCREAMING_SNAKE_CASE_    ='''\'ray[tune]\''''
   @staticmethod
   def       __a							(		):


        '''simple docstring'''
        return is_ray_available()
   def       __a							(		self      :	List[str]							,			snake_case__      :	List[Any]							,			snake_case__      :	int							,			snake_case__      :	str							,			**snake_case__      :	str							):


        '''simple docstring'''
        return run_hp_search_ray(snake_case__							,			snake_case__							,			snake_case__							,			**snake_case__							)




   def       __a							(		self      :	List[Any]							,			snake_case__      :	Tuple							):


        '''simple docstring'''
        return default_hp_space_ray(snake_case__							)




class 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    ='''sigopt'''
   @staticmethod
   def       __a							(		):


        '''simple docstring'''
        return is_sigopt_available()
   def       __a							(		self      :	List[str]							,			snake_case__      :	Optional[Any]							,			snake_case__      :	int							,			snake_case__      :	str							,			**snake_case__      :	Tuple							):


        '''simple docstring'''
        return run_hp_search_sigopt(snake_case__							,			snake_case__							,			snake_case__							,			**snake_case__							)




   def       __a							(		self      :	Tuple							,			snake_case__      :	int							):


        '''simple docstring'''
        return default_hp_space_sigopt(snake_case__							)




class 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    ='''wandb'''
   @staticmethod
   def       __a							(		):


        '''simple docstring'''
        return is_wandb_available()
   def       __a							(		self      :	int							,			snake_case__      :	Dict							,			snake_case__      :	int							,			snake_case__      :	str							,			**snake_case__      :	str							):


        '''simple docstring'''
        return run_hp_search_wandb(snake_case__							,			snake_case__							,			snake_case__							,			**snake_case__							)




   def       __a							(		self      :	List[str]							,			snake_case__      :	Optional[int]							):


        '''simple docstring'''
        return default_hp_space_wandb(snake_case__							)




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


def 	SCREAMING_SNAKE_CASE__       (  )->		str:






     '''simple docstring'''



     UpperCAmelCase__						:    str							=							[backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
     if len(snake_case				) > 0:
          UpperCAmelCase__						:    str							=							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()				)				)










"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCAmelCase	:	Tuple				=      {
    """configuration_lxmert""": ["""LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LxmertConfig"""],
    """tokenization_lxmert""": ["""LxmertTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase	:	int				=      ["""LxmertTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase	:	Tuple				=      [
     """LxmertEncoder""",
     """LxmertForPreTraining""",
     """LxmertForQuestionAnswering""",
     """LxmertModel""",
     """LxmertPreTrainedModel""",
     """LxmertVisualFeatureEncoder""",
     """LxmertXLayer""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase	:	Optional[int]				=      [
     """TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFLxmertForPreTraining""",
     """TFLxmertMainLayer""",
     """TFLxmertModel""",
     """TFLxmertPreTrainedModel""",
     """TFLxmertVisualFeatureEncoder""",
 ]


if TYPE_CHECKING:
 from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
 from .tokenization_lxmert import LxmertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_lxmert_fast import LxmertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_lxmert import (
      LxmertEncoder,
      LxmertForPreTraining,
      LxmertForQuestionAnswering,
      LxmertModel,
      LxmertPreTrainedModel,
      LxmertVisualFeatureEncoder,
      LxmertXLayer,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_lxmert import (
      TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFLxmertForPreTraining,
      TFLxmertMainLayer,
      TFLxmertModel,
      TFLxmertPreTrainedModel,
      TFLxmertVisualFeatureEncoder,
  )

else:
 import sys

 _lowerCAmelCase	:	Any				=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


