


'''simple docstring'''


import functools
import gc
import inspect

import torch

from .imports import is_npu_available, is_xpu_available







def 			snake_case_   (  *SCREAMING_SNAKE_CASE__     ):







				"""simple docstring"""





				if not isinstance(SCREAMING_SNAKE_CASE__							,      SCREAMING_SNAKE_CASE__     ):
								_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      list(SCREAMING_SNAKE_CASE__     )
				for i in range(len(SCREAMING_SNAKE_CASE__     )     ):
								_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      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 			snake_case_   (  SCREAMING_SNAKE_CASE__     ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      [
				    """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 			snake_case_   (  SCREAMING_SNAKE_CASE__ = None							,      SCREAMING_SNAKE_CASE__ = 128     ):







				"""simple docstring"""





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

				_SCREAMING_SNAKE_CASE :       Tuple     		=      starting_batch_size

				def decorator(*SCREAMING_SNAKE_CASE__							,      **SCREAMING_SNAKE_CASE__     ):
								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()
								_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      list(inspect.signature(SCREAMING_SNAKE_CASE__     ).parameters.keys()     )
								# Guard against user error
								if len(SCREAMING_SNAKE_CASE__     ) < (len(SCREAMING_SNAKE_CASE__     ) + 1):
												_SCREAMING_SNAKE_CASE :       Tuple     		=      """, """.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








'''simple docstring'''


import unittest

from knapsack import greedy_knapsack as kp





class     lowercase__  (						unittest.TestCase					):





							'''simple docstring'''


							def UpperCAmelCase_	(    self  ):
											_SCREAMING_SNAKE_CASE :       str     		=      [10, 20, 30, 40, 50, 60]
											_SCREAMING_SNAKE_CASE :       List[str]     		=      [2, 4, 6, 8, 10, 12]
											_SCREAMING_SNAKE_CASE :       str     		=      100
											self.assertEqual(kp.calc_profit(__snake_case    ,					__snake_case    ,					__snake_case  )    ,					210  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""max_weight must greater than zero."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""Weight can not be negative."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""Profit can not be negative."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""max_weight must greater than zero."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(
											    __snake_case    ,					"""The length of profit and weight must be same."""  )


if __name__ == "__main__":
				unittest.main()




