




"""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


_A													=      logging.get_logger(__name__)


class _lowerCamelCase    :
   _lowerCamelCase    :List[str]     				=     42
   _lowerCamelCase    :List[Any]     				=     None






   @staticmethod
   def 	_lowerCAmelCase   (		)			->						Union[str, Any]:

         """simple docstring"""
         raise NotImplementedError






   def 	_lowerCAmelCase   (		self       :		Any   ,     UpperCamelCase       :		Tuple   ,     UpperCamelCase       :		int   ,     UpperCamelCase       :		str   ,     **UpperCamelCase       :		Any   )			->						str:

         """simple docstring"""
         raise NotImplementedError






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		Optional[Any]   )			->						Union[str, Any]:

         """simple docstring"""
         raise NotImplementedError






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

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






class _lowerCamelCase    (					a_						):
   _lowerCamelCase    :Union[str, Any]     				=     "optuna"






   @staticmethod
   def 	_lowerCAmelCase   (		)			->						List[str]:

         """simple docstring"""
         return is_optuna_available()






   def 	_lowerCAmelCase   (		self       :		Any   ,     UpperCamelCase       :		Optional[Any]   ,     UpperCamelCase       :		int   ,     UpperCamelCase       :		str   ,     **UpperCamelCase       :		Optional[Any]   )			->						Tuple:

         """simple docstring"""
         return run_hp_search_optuna(_lowerCAmelCase   ,     _lowerCAmelCase   ,     _lowerCAmelCase   ,     **_lowerCAmelCase   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   ,     UpperCamelCase       :		Union[str, Any]   )			->						int:

         """simple docstring"""
         return default_hp_space_optuna(_lowerCAmelCase   )






class _lowerCamelCase    (					a_						):
   _lowerCamelCase    :Any     				=     "ray"
   _lowerCamelCase    :Any     				=     "'ray[tune]'"






   @staticmethod
   def 	_lowerCAmelCase   (		)			->						str:

         """simple docstring"""
         return is_ray_available()






   def 	_lowerCAmelCase   (		self       :		str   ,     UpperCamelCase       :		List[Any]   ,     UpperCamelCase       :		int   ,     UpperCamelCase       :		str   ,     **UpperCamelCase       :		int   )			->						List[Any]:

         """simple docstring"""
         return run_hp_search_ray(_lowerCAmelCase   ,     _lowerCAmelCase   ,     _lowerCAmelCase   ,     **_lowerCAmelCase   )






   def 	_lowerCAmelCase   (		self       :		Any   ,     UpperCamelCase       :		Any   )			->						str:

         """simple docstring"""
         return default_hp_space_ray(_lowerCAmelCase   )






class _lowerCamelCase    (					a_						):
   _lowerCamelCase    :Tuple     				=     "sigopt"






   @staticmethod
   def 	_lowerCAmelCase   (		)			->						Any:

         """simple docstring"""
         return is_sigopt_available()






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		Any   ,     UpperCamelCase       :		int   ,     UpperCamelCase       :		str   ,     **UpperCamelCase       :		str   )			->						str:

         """simple docstring"""
         return run_hp_search_sigopt(_lowerCAmelCase   ,     _lowerCAmelCase   ,     _lowerCAmelCase   ,     **_lowerCAmelCase   )






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		Dict   )			->						str:

         """simple docstring"""
         return default_hp_space_sigopt(_lowerCAmelCase   )






class _lowerCamelCase    (					a_						):
   _lowerCamelCase    :Union[str, Any]     				=     "wandb"






   @staticmethod
   def 	_lowerCAmelCase   (		)			->						List[str]:

         """simple docstring"""
         return is_wandb_available()






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		List[str]   ,     UpperCamelCase       :		int   ,     UpperCamelCase       :		str   ,     **UpperCamelCase       :		Optional[int]   )			->						List[str]:

         """simple docstring"""
         return run_hp_search_wandb(_lowerCAmelCase   ,     _lowerCAmelCase   ,     _lowerCAmelCase   ,     **_lowerCAmelCase   )






   def 	_lowerCAmelCase   (		self       :		List[str]   ,     UpperCamelCase       :		str   )			->						Tuple:

         """simple docstring"""
         return default_hp_space_wandb(_lowerCAmelCase   )






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



def 	lowercase_				(			)						->    List[Any]:
      lowerCAmelCase__      :			int   =	[backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
      if len(_lowerCAmelCase				) > 0:
            lowerCAmelCase__      :			int   =	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"""


from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType


class _lowerCamelCase    (					a_						):
   _lowerCamelCase    :Dict     				=     ["image_processor", "tokenizer"]
   _lowerCamelCase    :Dict     				=     "BlipImageProcessor"
   _lowerCamelCase    :Any     				=     ("BertTokenizer", "BertTokenizerFast")






   def __init__(		self       :		Dict   ,     UpperCamelCase       :		Optional[int]   ,     UpperCamelCase       :		Union[str, Any]   )			->						str:

         """simple docstring"""
         lowerCAmelCase__      :			Optional[Any]   =	False
         super().__init__(UpperCamelCase   ,     UpperCamelCase   )
         lowerCAmelCase__      :			List[Any]   =	self.image_processor






   def __call__(		self       :		int   ,     UpperCamelCase       :		ImageInput = None   ,     UpperCamelCase       :		Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None   ,     UpperCamelCase       :		bool = True   ,     UpperCamelCase       :		Union[bool, str, PaddingStrategy] = False   ,     UpperCamelCase       :		Union[bool, str, TruncationStrategy] = None   ,     UpperCamelCase       :		Optional[int] = None   ,     UpperCamelCase       :		int = 0   ,     UpperCamelCase       :		Optional[int] = None   ,     UpperCamelCase       :		Optional[bool] = None   ,     UpperCamelCase       :		bool = False   ,     UpperCamelCase       :		bool = False   ,     UpperCamelCase       :		bool = False   ,     UpperCamelCase       :		bool = False   ,     UpperCamelCase       :		bool = False   ,     UpperCamelCase       :		bool = True   ,     UpperCamelCase       :		Optional[Union[str, TensorType]] = None   ,     **UpperCamelCase       :		Optional[int]   ,     )			->						BatchEncoding:

         """simple docstring"""
         if images is None and text is None:
               raise ValueError("""You have to specify either images or text."""   )

         # Get only text
         if images is None:
               lowerCAmelCase__      :			Any   =	self.tokenizer
               lowerCAmelCase__      :			Optional[int]   =	self.tokenizer(
                   text=UpperCamelCase   ,     add_special_tokens=UpperCamelCase   ,     padding=UpperCamelCase   ,     truncation=UpperCamelCase   ,     max_length=UpperCamelCase   ,     stride=UpperCamelCase   ,     pad_to_multiple_of=UpperCamelCase   ,     return_attention_mask=UpperCamelCase   ,     return_overflowing_tokens=UpperCamelCase   ,     return_special_tokens_mask=UpperCamelCase   ,     return_offsets_mapping=UpperCamelCase   ,     return_token_type_ids=UpperCamelCase   ,     return_length=UpperCamelCase   ,     verbose=UpperCamelCase   ,     return_tensors=UpperCamelCase   ,     **UpperCamelCase   ,     )
               return text_encoding

         # add pixel_values
         lowerCAmelCase__      :			Tuple   =	self.image_processor(UpperCamelCase   ,     return_tensors=UpperCamelCase   )

         if text is not None:
               lowerCAmelCase__      :			Optional[int]   =	self.tokenizer(
                   text=UpperCamelCase   ,     add_special_tokens=UpperCamelCase   ,     padding=UpperCamelCase   ,     truncation=UpperCamelCase   ,     max_length=UpperCamelCase   ,     stride=UpperCamelCase   ,     pad_to_multiple_of=UpperCamelCase   ,     return_attention_mask=UpperCamelCase   ,     return_overflowing_tokens=UpperCamelCase   ,     return_special_tokens_mask=UpperCamelCase   ,     return_offsets_mapping=UpperCamelCase   ,     return_token_type_ids=UpperCamelCase   ,     return_length=UpperCamelCase   ,     verbose=UpperCamelCase   ,     return_tensors=UpperCamelCase   ,     **UpperCamelCase   ,     )
         else:
               lowerCAmelCase__      :			Tuple   =	None

         if text_encoding is not None:
               encoding_image_processor.update(UpperCamelCase   )

         return encoding_image_processor






   def 	_lowerCAmelCase   (		self       :		int   ,     *UpperCamelCase       :		Union[str, Any]   ,     **UpperCamelCase       :		List[str]   )			->						Dict:

         """simple docstring"""
         return self.tokenizer.batch_decode(*UpperCamelCase   ,     **UpperCamelCase   )






   def 	_lowerCAmelCase   (		self       :		List[Any]   ,     *UpperCamelCase       :		Tuple   ,     **UpperCamelCase       :		List[str]   )			->						List[Any]:

         """simple docstring"""
         return self.tokenizer.decode(*UpperCamelCase   ,     **UpperCamelCase   )






   @property
   def 	_lowerCAmelCase   (		self       :		List[Any]   )			->						Tuple:

         """simple docstring"""
         lowerCAmelCase__      :			Optional[int]   =	self.tokenizer.model_input_names
         lowerCAmelCase__      :			Union[str, Any]   =	self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )





