code: def benchmark(
      func,
      args=(),
      kwargs={},
      n_repeat=10000,
      *,
      name=None,
      n_warmup=10,
      max_duration=_math.inf,
      devices=None,
  ):
      """Timing utility for measuring time spent by both CPU and GPU.
  
      This function is a very convenient helper for setting up a timing test. The
      GPU time is properly recorded by synchronizing internal streams. As a
      result, to time a multi-GPU function all participating devices must be
      passed as the ``devices`` argument so that this helper knows which devices
      to record. A simple example is given as follows:
  
      .. code-block:: py
  
          import cupy as cp
          from cupyx.profiler import benchmark
  
          def f(a, b):
              return 3 * cp.sin(-a) * b
  
          a = 0.5 - cp.random.random((100,))
          b = cp.random.random((100,))
          print(benchmark(f, (a, b), n_repeat=1000))
  
  
      Args:
          func (callable): a callable object to be timed.
          args (tuple): positional argumens to be passed to the callable.
          kwargs (dict): keyword arguments to be passed to the callable.
          n_repeat (int): number of times the callable is called. Increasing
              this value would improve the collected statistics at the cost
              of longer test time.
          name (str): the function name to be reported. If not given, the
              callable's ``__name__`` attribute is used.
          n_warmup (int): number of times the callable is called. The warm-up
              runs are not timed.
          max_duration (float): the maximum time (in seconds) that the entire
              test can use. If the taken time is longer than this limit, the test
              is stopped and the statistics collected up to the breakpoint is
              reported.
          devices (tuple): a tuple of device IDs (int) that will be timed during
              the timing test. If not given, the current device is used.
  
      Returns:
          :class:`~cupyx.profiler._time._PerfCaseResult`:
              an object collecting all test results.
  
      """
  
      if name is None:
          name = func.__name__
  
      if devices is None:
          devices = (_cupy.cuda.get_device_id(),)
  
      if not callable(func):
          raise ValueError("`func` should be a callable object.")
      if not isinstance(args, tuple):
          raise ValueError("`args` should be of tuple type.")
      if not isinstance(kwargs, dict):
          raise ValueError("`kwargs` should be of dict type.")
      if not isinstance(n_repeat, int):
          raise ValueError("`n_repeat` should be an integer.")
      if not isinstance(name, str):
          raise ValueError("`name` should be a string.")
      if not isinstance(n_warmup, int):
          raise ValueError("`n_warmup` should be an integer.")
      if not _numpy.isreal(max_duration):
          raise ValueError("`max_duration` should be given in seconds")
      if not isinstance(devices, tuple):
          raise ValueError("`devices` should be of tuple type")
  
      return _repeat(
          func,
          args,
          kwargs,
          n_repeat,
          name,
          n_warmup,
          max_duration,
          devices,
      )
  
file_path: cupy/cupyx/profiler/_time.py
imports: import math
  import time
  import numpy
  import cupy
  from cupy_backends.cuda.api import runtime
label_desc: Use image node_id 1 for calling a global function with example usage: benchmark(func, args, kwargs, n_repeat) and returns: _repeat