

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

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



@dataclass(frozen=__SCREAMING_SNAKE_CASE				)
class     A__(__SCREAMING_SNAKE_CASE				):
						"""simple docstring"""






						_A  :							str     =       field(default='''automatic-speech-recognition''',   metadata={'''include_in_asdict_even_if_is_default''': True}				)
						_A  :							ClassVar[Features]     =       Features({'''audio''': Audio()}				)
						_A  :							ClassVar[Features]     =       Features({'''transcription''': Value('''string'''				)}				)
						_A  :							str     =       "audio"
						_A  :							str     =       "transcription"





						def        UpperCamelCase__ (  self   ,	_lowercase  )			->      int:
									if self.audio_column not in features:
												raise ValueError(F'''Column {self.audio_column} is not present in features.'''  )
									if not isinstance(features[self.audio_column]   ,	_lowercase  ):
												raise ValueError(F'''Column {self.audio_column} is not an Audio type.'''  )
									a_		:		Optional[Any]      				=      copy.deepcopy(self  )
									a_		:		List[Any]      				=      self.input_schema.copy()
									a_		:		Tuple      				=      features[self.audio_column]
									a_		:		int      				=      input_schema
									return task_template





						@property
						def        UpperCamelCase__ (  self  )			->      Optional[int]:
									return {self.audio_column: "audio", self.transcription_column: "transcription"}




_lowerCamelCase					   ={
    "joule": 1.0,
    "kilojoule": 1_0_0_0,
    "megajoule": 1_0_0_0_0_0_0,
    "gigajoule": 1_0_0_0_0_0_0_0_0_0,
    "wattsecond": 1.0,
    "watthour": 3_6_0_0,
    "kilowatthour": 3_6_0_0_0_0_0,
    "newtonmeter": 1.0,
    "calorie_nutr": 4_1_8_6.8,
    "kilocalorie_nutr": 4_1_8_6_8_0_0.0_0,
    "electronvolt": 1.6_0_2_1_7_6_6_3_4E-1_9,
    "britishthermalunit_it": 1_0_5_5.0_5_5_8_5,
    "footpound": 1.355818,
}





def     _a					(						lowerCamelCase,	lowerCamelCase,	lowerCamelCase							):
 if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
  lowerCamelCase		:	Dict							=      (
      F'''Incorrect \'from_type\' or \'to_type\' value: {from_type!r}, {to_type!r}\n'''
      F'''Valid values are: {", ".join(lowerCamelCase							)}'''
  )
  raise ValueError(lowerCamelCase							)
 return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
      import doctest

      doctest.testmod()




