'''simple docstring'''


from __future__ import annotations

import sys


def    _lowerCamelCase       ( lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int  ):



     """simple docstring"""





     if abs(lowerCamelCase_  ) == 1:
          return a, 0
     elif abs(lowerCamelCase_  ) == 1:
          return 0, b

     UpperCAmelCase_				:  Union[str, Any]  = a, b
     UpperCAmelCase_				:  Optional[int]  = 1, 0
     UpperCAmelCase_				:  Dict  = 0, 1

     while remainder != 0:
          UpperCAmelCase_				:  Optional[int]  = old_remainder // remainder
          UpperCAmelCase_				:  List[str]  = remainder, old_remainder - quotient * remainder
          UpperCAmelCase_				:  List[str]  = coeff_a, old_coeff_a - quotient * coeff_a
          UpperCAmelCase_				:  Any  = coeff_b, old_coeff_b - quotient * coeff_b

     # sign correction for negative numbers
     if a < 0:
          UpperCAmelCase_				:  Optional[int]  = -old_coeff_a
     if b < 0:
          UpperCAmelCase_				:  Tuple  = -old_coeff_b

     return old_coeff_a, old_coeff_b


def    _lowerCamelCase       ( ):



     """simple docstring"""





     if len(sys.argv  ) < 3:
          print('2 integer arguments required'  )
          return 1
     UpperCAmelCase_				:  List[str]  = int(sys.argv[1]  )
     UpperCAmelCase_				:  Any  = int(sys.argv[2]  )
     print(extended_euclidean_algorithm(lowerCamelCase_      ,	lowerCamelCase_  )  )
     return 0


if __name__ == "__main__":
 raise SystemExit(main())














from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


UpperCAmelCase_					:		int           = {
    '''configuration_unispeech_sat''': ['''UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechSatConfig'''],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase_					:		Tuple           = [
	    '''UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''UniSpeechSatForAudioFrameClassification''',
	    '''UniSpeechSatForCTC''',
	    '''UniSpeechSatForPreTraining''',
	    '''UniSpeechSatForSequenceClassification''',
	    '''UniSpeechSatForXVector''',
	    '''UniSpeechSatModel''',
	    '''UniSpeechSatPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_unispeech_sat import (
		    UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    UniSpeechSatForAudioFrameClassification,
		    UniSpeechSatForCTC,
		    UniSpeechSatForPreTraining,
		    UniSpeechSatForSequenceClassification,
		    UniSpeechSatForXVector,
		    UniSpeechSatModel,
		    UniSpeechSatPreTrainedModel,
		)

else:
	import sys

	UpperCAmelCase_					:		str           = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
