






from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate





@dataclass(frozen=A__	)
class       __a  (   A__	):
 _lowerCAmelCase	:	str				=			field(default='''language-modeling'''	,       metadata={'''include_in_asdict_even_if_is_default''': True}	)

 _lowerCAmelCase	:	ClassVar[Features]				=			Features({'''text''': Value('''string'''	)}	)
 _lowerCAmelCase	:	ClassVar[Features]				=			Features({}	)
 _lowerCAmelCase	:	str				=			"text"







 @property
 def  __lowercase (		self :       str						):


      '''simple docstring'''






      return {self.text_column: "text"}







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase     :							Dict    =logging.get_logger(__name__)





class       __a  (   A__	):
 _lowerCAmelCase	:	Optional[int]				=			'''timm_backbone'''







 def __init__(		self :       Dict							,       SCREAMING_SNAKE_CASE :       Dict=None							,       SCREAMING_SNAKE_CASE :       List[Any]=3							,       SCREAMING_SNAKE_CASE :       List[Any]=True							,       SCREAMING_SNAKE_CASE :       Dict=True							,       SCREAMING_SNAKE_CASE :       Union[str, Any]=None							,       **SCREAMING_SNAKE_CASE :       int							,       ):


      '''simple docstring'''






      super().__init__(**SCREAMING_SNAKE_CASE						)
      UpperCamelCase__      :       Union[str, Any]	    =  backbone
      UpperCamelCase__      :       Dict	    =  num_channels
      UpperCamelCase__      :       str	    =  features_only
      UpperCamelCase__      :       Dict	    =  use_pretrained_backbone
      UpperCamelCase__      :       Tuple	    =  True
      UpperCamelCase__      :       List[Any]	    =  out_indices if out_indices is not None else (-1,)