def lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     ):
				'''simple docstring'''







				if a < 0 or b < 0:
								raise ValueError('''the value of both inputs must be positive'''     )

				__UpperCamelCase					:Optional[Any]        =		str(bin(SCREAMING_SNAKE_CASE     )     )[2:]  # remove the leading "0b"
				__UpperCamelCase					:Optional[Any]        =		str(bin(SCREAMING_SNAKE_CASE     )     )[2:]  # remove the leading "0b"

				__UpperCamelCase					:Union[str, Any]        =		max(len(SCREAMING_SNAKE_CASE     )  ,      len(SCREAMING_SNAKE_CASE     )     )

				return "0b" + "".join(
				    str(int(char_a != char_b     )     )
				    for char_a, char_b in zip(a_binary.zfill(SCREAMING_SNAKE_CASE     )  ,      b_binary.zfill(SCREAMING_SNAKE_CASE     )     )     )


if __name__ == "__main__":
				import doctest

				doctest.testmod()






from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
    if not (is_transformers_available() and is_torch_available()):
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
    from .notes_encoder import SpectrogramNotesEncoder
    from .continous_encoder import SpectrogramContEncoder
    from .pipeline_spectrogram_diffusion import (
        SpectrogramContEncoder,
        SpectrogramDiffusionPipeline,
        TaFilmDecoder,
    )

try:
    if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
    from .midi_utils import MidiProcessor





