
import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union





class   __UpperCamelCase				(    enum.Enum   ):






     """simple docstring"""







     lowerCAmelCase_     =	'''timm'''
     lowerCAmelCase_     =	'''transformers'''






def     a__			(    snake_case   ,	snake_case   ,	snake_case    ):





  """simple docstring"""
  if stage_names is None:
    raise ValueError('''Stage_names must be set for transformers backbones'''    )

  if out_features is not None:
    if not isinstance(snake_case   ,	(list,)    ):
      raise ValueError(F'''out_features must be a list {type(snake_case    )}'''    )
    if any(feat not in stage_names for feat in out_features    ):
      raise ValueError(F'''out_features must be a subset of stage_names: {stage_names} got {out_features}'''    )

  if out_indices is not None:
    if not isinstance(snake_case   ,	(list, tuple)    ):
      raise ValueError(F'''out_indices must be a list or tuple, got {type(snake_case    )}'''    )
    if any(idx >= len(snake_case    ) for idx in out_indices    ):
      raise ValueError('''out_indices must be valid indices for stage_names {stage_names}, got {out_indices}'''    )

  if out_features is not None and out_indices is not None:
    if len(snake_case    ) != len(snake_case    ):
      raise ValueError('''out_features and out_indices should have the same length if both are set'''    )
    if out_features != [stage_names[idx] for idx in out_indices]:
      raise ValueError('''out_features and out_indices should correspond to the same stages if both are set'''    )


def     a__			(    snake_case   ,	snake_case   ,	snake_case   ,	):





  """simple docstring"""
  if out_indices is None and out_features is None:
    __SCREAMING_SNAKE_CASE     :					Any			=						[len(snake_case    ) - 1]
    __SCREAMING_SNAKE_CASE     :					str			=						[stage_names[-1]]
  elif out_indices is None and out_features is not None:
    __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						[stage_names.index(snake_case    ) for layer in out_features]
  elif out_features is None and out_indices is not None:
    __SCREAMING_SNAKE_CASE     :					List[str]			=						[stage_names[idx] for idx in out_indices]
  return out_features, out_indices


def     a__			(    snake_case   ,	snake_case   ,	snake_case   ,	):





  """simple docstring"""
  verify_out_features_out_indices(out_features=snake_case   ,	out_indices=snake_case   ,	stage_names=snake_case    )
  __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					List[Any]			=						_align_output_features_output_indices(
      out_features=snake_case   ,	out_indices=snake_case   ,	stage_names=snake_case    )
  # Verify that the aligned out_features and out_indices are valid
  verify_out_features_out_indices(out_features=snake_case   ,	out_indices=snake_case   ,	stage_names=snake_case    )
  return output_features, output_indices





class   __UpperCamelCase				:






     """simple docstring"""







     lowerCAmelCase_     =	None



     def 				UpperCAmelCase__    (							self    :    Dict      ,		_A    :    int				):







       """simple docstring"""




       if getattr(self      ,		'''_backbone'''      ,		_A				) is None:
         raise ValueError('''self._backbone must be set before calling _init_timm_backbone'''				)

       # These will diagree with the defaults for the transformers models e.g. for resnet50
       # the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
       # the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
       __SCREAMING_SNAKE_CASE     :					str			=						[stage['''module'''] for stage in self._backbone.feature_info.info]
       __SCREAMING_SNAKE_CASE     :					Dict			=						[stage['''num_chs'''] for stage in self._backbone.feature_info.info]
       __SCREAMING_SNAKE_CASE     :					int			=						self._backbone.feature_info.out_indices
       __SCREAMING_SNAKE_CASE     :					Tuple			=						self._backbone.feature_info.module_name()

       # We verify the out indices and out features are valid
       verify_out_features_out_indices(
           out_features=_A      ,		out_indices=_A      ,		stage_names=self.stage_names				)
       __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					str			=						out_features, out_indices



     def 				UpperCAmelCase__    (							self    :    Optional[Any]      ,		_A    :    Any				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						getattr(_A      ,		'''stage_names'''				)
       __SCREAMING_SNAKE_CASE     :					Dict			=						getattr(_A      ,		'''out_features'''      ,		_A				)
       __SCREAMING_SNAKE_CASE     :					str			=						getattr(_A      ,		'''out_indices'''      ,		_A				)

       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						stage_names
       __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					Dict			=						get_aligned_output_features_output_indices(
           out_features=_A      ,		out_indices=_A      ,		stage_names=_A				)
       # Number of channels for each stage. This is set in the transformer backbone model init
       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						None



     def 				UpperCAmelCase__    (							self    :    List[Any]      ,		_A    :    Tuple				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					List[str]			=						config

       __SCREAMING_SNAKE_CASE     :					Dict			=						getattr(_A      ,		'''use_timm_backbone'''      ,		_A				)
       __SCREAMING_SNAKE_CASE     :					List[str]			=						BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

       if self.backbone_type == BackboneType.TIMM:
         self._init_timm_backbone(_A				)
       elif self.backbone_type == BackboneType.TRANSFORMERS:
         self._init_transformers_backbone(_A				)
       else:
         raise ValueError(F'''backbone_type {self.backbone_type} not supported.'''				)



     @property
     def 				UpperCAmelCase__    (							self    :    Optional[int]				):







       """simple docstring"""




       return self._out_features



     @out_features.setter
     def 				UpperCAmelCase__    (							self    :    Tuple      ,		_A    :    List[str]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					Any			=						get_aligned_output_features_output_indices(
           out_features=_A      ,		out_indices=_A      ,		stage_names=self.stage_names				)



     @property
     def 				UpperCAmelCase__    (							self    :    Dict				):







       """simple docstring"""




       return self._out_indices



     @out_indices.setter
     def 				UpperCAmelCase__    (							self    :    str      ,		_A    :    Union[Tuple[int], List[int]]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					List[str]			=						get_aligned_output_features_output_indices(
           out_features=_A      ,		out_indices=_A      ,		stage_names=self.stage_names				)



     @property
     def 				UpperCAmelCase__    (							self    :    Dict				):







       """simple docstring"""




       return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names				)}



     @property
     def 				UpperCAmelCase__    (							self    :    Dict				):







       """simple docstring"""




       return [self.out_feature_channels[name] for name in self.out_features]



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







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					int			=						dict(inspect.signature(self.forward				).parameters				)
       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						{k: v for k, v in kwargs.items() if k in signature}
       return self(*_A      ,		**_A				)



     def 				UpperCAmelCase__    (							self    :    Optional[int]      ,		_A    :    Union[str, Any]      ,		_A    :    Optional[bool] = None      ,		_A    :    Optional[bool] = None      ,		_A    :    Optional[bool] = None      ,		):







       """simple docstring"""




       raise NotImplementedError('''This method should be implemented by the derived class.'''				)




     def 				UpperCAmelCase__    (							self    :    str				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						super().to_dict()
       __SCREAMING_SNAKE_CASE     :					str			=						output.pop('''_out_features'''				)
       __SCREAMING_SNAKE_CASE     :					str			=						output.pop('''_out_indices'''				)
       return output






class   __UpperCamelCase				:






     """simple docstring"""







     @property
     def 				UpperCAmelCase__    (							self    :    List[str]				):







       """simple docstring"""




       return self._out_features



     @out_features.setter
     def 				UpperCAmelCase__    (							self    :    List[Any]      ,		_A    :    List[str]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					Optional[int]			=						get_aligned_output_features_output_indices(
           out_features=_A      ,		out_indices=_A      ,		stage_names=self.stage_names				)



     @property
     def 				UpperCAmelCase__    (							self    :    Union[str, Any]				):







       """simple docstring"""




       return self._out_indices



     @out_indices.setter
     def 				UpperCAmelCase__    (							self    :    Tuple      ,		_A    :    Union[Tuple[int], List[int]]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					Tuple			=						get_aligned_output_features_output_indices(
           out_features=_A      ,		out_indices=_A      ,		stage_names=self.stage_names				)




     def 				UpperCAmelCase__    (							self    :    Optional[Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					int			=						super().to_dict()
       __SCREAMING_SNAKE_CASE     :					str			=						output.pop('''_out_features'''				)
       __SCREAMING_SNAKE_CASE     :					Dict			=						output.pop('''_out_indices'''				)
       return output


from typing import Optional

from ..utils.logging import get_logger
from .audio_classificiation import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModeling
from .question_answering import QuestionAnsweringExtractive
from .summarization import Summarization
from .text_classification import TextClassification


lowercase_											=	[
    """AutomaticSpeechRecognition""",
    """AudioClassification""",
    """ImageClassification""",
    """LanguageModeling""",
    """QuestionAnsweringExtractive""",
    """Summarization""",
    """TaskTemplate""",
    """TextClassification""",
]

lowercase_											=	get_logger(__name__)


lowercase_											=	{
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					str			=						task_template_dict.get('''task'''    )
  if task_name is None:
    logger.warning(F'''Couldn\'t find template for task \'{task_name}\'. Available templates: {list(snake_case    )}'''    )
    return None
  __SCREAMING_SNAKE_CASE     :					Any			=						NAMEaTEMPLATE.get(snake_case    )
  return template.from_dict(snake_case    )
