import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin




class        lowercase_  (  UpperCamelCase_						):



	"""simple docstring"""





	UpperCAmelCase_  : List[Any]       =    ["""image_processor""", """tokenizer"""]
	UpperCAmelCase_  : List[str]       =    """AutoImageProcessor"""
	UpperCAmelCase_  : Any       =    """AutoTokenizer"""


	def __init__(							self		,      __SCREAMING_SNAKE_CASE=None		,      __SCREAMING_SNAKE_CASE=None		,      **__SCREAMING_SNAKE_CASE    )						->Optional[int]:
								lowerCAmelCase     		=		None
								if "feature_extractor" in kwargs:
															warnings.warn(
															    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
															    ''' instead.'''		,      __SCREAMING_SNAKE_CASE		,      )
															lowerCAmelCase     		=		kwargs.pop('''feature_extractor'''    )

								lowerCAmelCase     		=		image_processor if image_processor is not None else feature_extractor
								if image_processor is None:
															raise ValueError('''You need to specify an `image_processor`.'''    )
								if tokenizer is None:
															raise ValueError('''You need to specify a `tokenizer`.'''    )

								super().__init__(__SCREAMING_SNAKE_CASE		,      __SCREAMING_SNAKE_CASE    )
								lowerCAmelCase     		=		self.image_processor
								lowerCAmelCase     		=		False


	def __call__(							self		,      *__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )						->Optional[Any]:
								# For backward compatibility
								if self._in_target_context_manager:
															return self.current_processor(*__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )

								lowerCAmelCase     		=		kwargs.pop('''images'''		,      __SCREAMING_SNAKE_CASE    )
								lowerCAmelCase     		=		kwargs.pop('''text'''		,      __SCREAMING_SNAKE_CASE    )
								if len(__SCREAMING_SNAKE_CASE    ) > 0:
															lowerCAmelCase     		=		args[0]
															lowerCAmelCase     		=		args[1:]

								if images is None and text is None:
															raise ValueError('''You need to specify either an `images` or `text` input to process.'''    )

								if images is not None:
															lowerCAmelCase     		=		self.image_processor(__SCREAMING_SNAKE_CASE		,      *__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )
								if text is not None:
															lowerCAmelCase     		=		self.tokenizer(__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )

								if text is None:
															return inputs
								elif images is None:
															return encodings
								else:
															lowerCAmelCase     		=		encodings['''input_ids''']
															return inputs


	def       SCREAMING_SNAKE_CASE_    (							self		,      *__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )						->List[str]:
								return self.tokenizer.batch_decode(*__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )


	def       SCREAMING_SNAKE_CASE_    (							self		,      *__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )						->Tuple:
								return self.tokenizer.decode(*__SCREAMING_SNAKE_CASE		,      **__SCREAMING_SNAKE_CASE    )


	@contextmanager
	def       SCREAMING_SNAKE_CASE_    (							self    )						->Dict:
								warnings.warn(
								    '''`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '''
								    '''labels by using the argument `text` of the regular `__call__` method (either in the same call as '''
								    '''your images inputs, or in a separate call.'''    )
								lowerCAmelCase     		=		True
								lowerCAmelCase     		=		self.tokenizer
								yield
								lowerCAmelCase     		=		self.image_processor
								lowerCAmelCase     		=		False


	@property
	def       SCREAMING_SNAKE_CASE_    (							self    )						->List[Any]:
								warnings.warn(
								    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''		,      __SCREAMING_SNAKE_CASE		,      )
								return self.image_processor_class




	@property
	def       SCREAMING_SNAKE_CASE_    (							self    )						->Union[str, Any]:
								warnings.warn(
								    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''		,      __SCREAMING_SNAKE_CASE		,      )
								return self.image_processor




lowercase__      :    dict[str, float]          =     {
    "kilogram": 1,
    "gram": pow(1_0, 3),
    "milligram": pow(1_0, 6),
    "metric-ton": pow(1_0, -3),
    "long-ton": 0.0_0_0_9_8_4_2_0_7_3,
    "short-ton": 0.0_0_1_1_0_2_3_1_2_2,
    "pound": 2.2_0_4_6_2_4_4_2_0_2,
    "stone": 0.1_5_7_4_7_3_1_7_2_8,
    "ounce": 3_5.2_7_3_9_9_0_7_2_3,
    "carrat": 5_0_0_0,
    "atomic-mass-unit": 6.0_22_13_66_52e26,
}

lowercase__      :    dict[str, float]          =     {
    "kilogram": 1,
    "gram": pow(1_0, -3),
    "milligram": pow(1_0, -6),
    "metric-ton": pow(1_0, 3),
    "long-ton": 1_0_1_6.0_4_6_0_8,
    "short-ton": 9_0_7.1_8_4,
    "pound": 0.4_5_3_5_9_2,
    "stone": 6.3_5_0_2_9,
    "ounce": 0.0_2_8_3_4_9_5,
    "carrat": 0.0_0_0_2,
    "atomic-mass-unit": 1.6_60_54_01_99e-27,
}

def        SCREAMING_SNAKE_CASE_					(						snake_case__       ,  snake_case__       ,  snake_case__							)					->     float:
							if to_type not in KILOGRAM_CHART or from_type not in WEIGHT_TYPE_CHART:
														lowerCAmelCase     		=		(
														    f"Invalid 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"
														    f"Supported values are: {', '.join(snake_case__							)}"
														)
														raise ValueError(snake_case__							)
							return value * KILOGRAM_CHART[to_type] * WEIGHT_TYPE_CHART[from_type]


if __name__ == "__main__":
	import doctest

	doctest.testmod()



