





import functools
import gc
import inspect

import torch

from .imports import is_npu_available, is_xpu_available



def 				lowerCAmelCase_ (							*A_):
    if not isinstance(A_    ,A_):
        UpperCamelCase__:	Any					=     list(A_)
    for i in range(len(A_)):
        UpperCamelCase__:	List[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 				lowerCAmelCase_ (							A_):
    UpperCamelCase__:	Tuple					=     [
        "CUDA out of memory.",  # CUDA OOM
        "cuDNN error: CUDNN_STATUS_NOT_SUPPORTED.",  # CUDNN SNAFU
        "DefaultCPUAllocator: can't allocate memory",  # CPU OOM
    ]
    if isinstance(A_    ,A_) and len(exception.args) == 1:
        return any(err in exception.args[0] for err in _statements)
    return False




def 				lowerCAmelCase_ (							A_ = None    ,A_ = 1_28):
    if function is None:
        return functools.partial(A_    ,starting_batch_size=A_)

    UpperCamelCase__:	Union[str, Any]					=     starting_batch_size

    def decorator(*A_    ,**A_):
        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[Any]					=     list(inspect.signature(A_).parameters.keys())
        # Guard against user error
        if len(A_) < (len(A_) + 1):
            UpperCamelCase__:	List[str]					=     ", ".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(A_    ,*A_    ,**A_)
            except Exception as e:
                if should_reduce_batch_size(A_):
                    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








import unittest

from knapsack import knapsack as k




class        _a    (    unittest.TestCase):

      """simple docstring"""


      def 			UpperCAmelCase_       (		self:			Union[str, Any]					):
          '''simple docstring'''


          UpperCamelCase__:	Tuple					=     0
          UpperCamelCase__:	Optional[int]					=     [0]
          UpperCamelCase__:	Dict					=     [0]
          UpperCamelCase__:	str					=     len(__lowerCamelCase					)
          self.assertEqual(k.knapsack(__lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase					)	,    0					)

          UpperCamelCase__:	Tuple					=     [60]
          UpperCamelCase__:	List[Any]					=     [10]
          UpperCamelCase__:	Any					=     len(__lowerCamelCase					)
          self.assertEqual(k.knapsack(__lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase					)	,    0					)






      def 			UpperCAmelCase_       (		self:			Any					):
          '''simple docstring'''


          UpperCamelCase__:	List[str]					=     3
          UpperCamelCase__:	Any					=     [1, 2, 3]
          UpperCamelCase__:	Dict					=     [3, 2, 1]
          UpperCamelCase__:	List[str]					=     len(__lowerCamelCase					)
          self.assertEqual(k.knapsack(__lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase					)	,    5					)






      def 			UpperCAmelCase_       (		self:			List[Any]					):
          '''simple docstring'''


          UpperCamelCase__:	List[str]					=     50
          UpperCamelCase__:	Optional[Any]					=     [60, 100, 120]
          UpperCamelCase__:	Optional[Any]					=     [10, 20, 30]
          UpperCamelCase__:	Any					=     len(__lowerCamelCase					)
          self.assertEqual(k.knapsack(__lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase	,    __lowerCamelCase					)	,    220					)


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

