





def 					SCREAMING_SNAKE_CASE__				(							UpperCamelCase__:				list     ):
		if any(not isinstance(UpperCamelCase__       , UpperCamelCase__     ) or x < 0 for x in sequence     ):
				raise TypeError("""Sequence must be list of non-negative integers"""     )
		for _ in range(len(UpperCamelCase__     )     ):
				for i, (rod_upper, rod_lower) in enumerate(zip(UpperCamelCase__       , sequence[1:]     )     ):
						if rod_upper > rod_lower:
								sequence[i] -= rod_upper - rod_lower
								sequence[i + 1] += rod_upper - rod_lower
		return sequence


if __name__ == "__main__":
	assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
	assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


_lowerCamelCase 					=      {'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase 					=      ['SpeechEncoderDecoderModel']

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase 					=      ['FlaxSpeechEncoderDecoderModel']

if TYPE_CHECKING:
	from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
	import sys

	_lowerCamelCase 					=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)