


from __future__ import annotations






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		list[int]       ,  SCREAMING_SNAKE_CASE_   :		int       ,  SCREAMING_SNAKE_CASE_   :		int       ,  SCREAMING_SNAKE_CASE_   :		int	):





			"""simple docstring"""




			if (direction == 1 and array[indexa] > array[indexa]) or (
			    direction == 0 and array[indexa] < array[indexa]
			):
						UpperCamelCase  ,  UpperCamelCase         =					array[indexa], array[indexa]






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		list[int]       ,  SCREAMING_SNAKE_CASE_   :		int       ,  SCREAMING_SNAKE_CASE_   :		int       ,  SCREAMING_SNAKE_CASE_   :		int	):





			"""simple docstring"""




			if length > 1:
						UpperCamelCase         =					int(length / 2	)
						for i in range(SCREAMING_SNAKE_CASE_       ,  low + middle	):
									comp_and_swap(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  i + middle       ,  SCREAMING_SNAKE_CASE_	)
						bitonic_merge(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_	)
						bitonic_merge(SCREAMING_SNAKE_CASE_       ,  low + middle       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_	)






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		list[int]       ,  SCREAMING_SNAKE_CASE_   :		int       ,  SCREAMING_SNAKE_CASE_   :		int       ,  SCREAMING_SNAKE_CASE_   :		int	):





			"""simple docstring"""




			if length > 1:
						UpperCamelCase         =					int(length / 2	)
						bitonic_sort(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  1	)
						bitonic_sort(SCREAMING_SNAKE_CASE_       ,  low + middle       ,  SCREAMING_SNAKE_CASE_       ,  0	)
						bitonic_merge(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_	)


if __name__ == "__main__":
			__snake_case            =   input("Enter numbers separated by a comma:\n").strip()
			__snake_case            =   [int(item.strip()) for item in user_input.split(",")]

			bitonic_sort(unsorted, 0, len(unsorted), 1)
			print("\nSorted array in ascending order is: ", end="")
			print(*unsorted, sep=", ")

			bitonic_merge(unsorted, 0, len(unsorted), 0)
			print("Sorted array in descending order is: ", end="")
			print(*unsorted, sep=", ")








import functools
import gc
import inspect

import torch

from .imports import is_npu_available, is_xpu_available






def 							_lowercase    (		*SCREAMING_SNAKE_CASE_   :		List[Any]	):





			"""simple docstring"""




			if not isinstance(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_	):
						UpperCamelCase         =					list(SCREAMING_SNAKE_CASE_	)
			for i in range(len(SCREAMING_SNAKE_CASE_	)	):
						UpperCamelCase         =					None
			gc.collect()
			if is_xpu_available():
						torch.xpu.empty_cache()
			elif is_npu_available():
						torch.npu.empty_cache()
			else:
						torch.cuda.empty_cache()
			return objects






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		Exception	):





			"""simple docstring"""




			UpperCamelCase         =					[
			    """CUDA out of memory.""",  # CUDA OOM
			    """cuDNN error: CUDNN_STATUS_NOT_SUPPORTED.""",  # CUDNN SNAFU
			    """DefaultCPUAllocator: can't allocate memory""",  # CPU OOM
			]
			if isinstance(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_	) and len(exception.args	) == 1:
						return any(err in exception.args[0] for err in _statements	)
			return False






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		callable = None       ,  SCREAMING_SNAKE_CASE_   :		int = 128	):





			"""simple docstring"""




			if function is None:
						return functools.partial(SCREAMING_SNAKE_CASE_       ,  starting_batch_size=SCREAMING_SNAKE_CASE_	)

			UpperCamelCase         =					starting_batch_size

			def decorator(*SCREAMING_SNAKE_CASE_   :		Union[str, Any]       ,  **SCREAMING_SNAKE_CASE_   :		Tuple	):
						nonlocal batch_size
						gc.collect()
						if is_xpu_available():
									torch.xpu.empty_cache()
						elif is_npu_available():
									torch.npu.empty_cache()
						else:
									torch.cuda.empty_cache()
						UpperCamelCase         =					list(inspect.signature(SCREAMING_SNAKE_CASE_	).parameters.keys()	)
						# Guard against user error
						if len(SCREAMING_SNAKE_CASE_	) < (len(SCREAMING_SNAKE_CASE_	) + 1):
									UpperCamelCase         =					""", """.join([f'{arg}={value}' for arg, value in zip(params[1:]       ,  args[1:]	)]	)
									raise TypeError(
									    f'Batch size was passed into `{function.__name__}` as the first argument when called.'
									    f'Remove this as the decorator already does so: `{function.__name__}({arg_str})`'	)
						while True:
									if batch_size == 0:
												raise RuntimeError("""No executable batch size found, reached zero."""	)
									try:
												return function(SCREAMING_SNAKE_CASE_       ,  *SCREAMING_SNAKE_CASE_       ,  **SCREAMING_SNAKE_CASE_	)
									except Exception as e:
												if should_reduce_batch_size(SCREAMING_SNAKE_CASE_	):
															gc.collect()
															if is_xpu_available():
																		torch.xpu.empty_cache()
															elif is_npu_available():
																		torch.npu.empty_cache()
															else:
																		torch.cuda.empty_cache()
															batch_size //= 2
												else:
															raise

			return decorator




