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According to the user guide, when manual timing, it is necessary to explicit it by using the `UseManualTime` function. Its equivalent in Python is use_manual_time(). This function was not called in the example. It is possible to verify that the use of this function has an impact on the measure by adding another `time.sleep(0.01)` at the end of the iteration. There is a x2 difference depending on whether `use_manual_time()` is used or not. Co-authored-by: dominic <510002+dmah42@users.noreply.github.com>
141 lines
3.8 KiB
Python
141 lines
3.8 KiB
Python
# Copyright 2020 Google Inc. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Example of Python using C++ benchmark framework.
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To run this example, you must first install the `google_benchmark` Python package.
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To install using `setup.py`, download and extract the `google_benchmark` source.
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In the extracted directory, execute:
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python setup.py install
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"""
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import random
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import time
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import google_benchmark as benchmark
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from google_benchmark import Counter
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@benchmark.register
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def empty(state):
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while state:
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pass
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@benchmark.register
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def sum_million(state):
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while state:
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sum(range(1_000_000))
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@benchmark.register
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def pause_timing(state):
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"""Pause timing every iteration."""
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while state:
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# Construct a list of random ints every iteration without timing it
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state.pause_timing()
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random_list = [random.randint(0, 100) for _ in range(100)]
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state.resume_timing()
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# Time the in place sorting algorithm
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random_list.sort()
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@benchmark.register
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def skipped(state):
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if True: # Test some predicate here.
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state.skip_with_error("some error")
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return # NOTE: You must explicitly return, or benchmark will continue.
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... # Benchmark code would be here.
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@benchmark.register
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@benchmark.option.use_manual_time()
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def manual_timing(state):
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while state:
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# Manually count Python CPU time
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start = time.perf_counter() # perf_counter_ns() in Python 3.7+
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# Something to benchmark
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time.sleep(0.01)
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end = time.perf_counter()
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state.set_iteration_time(end - start)
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@benchmark.register
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def custom_counters(state):
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"""Collect custom metric using benchmark.Counter."""
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num_foo = 0.0
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while state:
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# Benchmark some code here
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pass
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# Collect some custom metric named foo
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num_foo += 0.13
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# Automatic Counter from numbers.
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state.counters["foo"] = num_foo
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# Set a counter as a rate.
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state.counters["foo_rate"] = Counter(num_foo, Counter.kIsRate)
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# Set a counter as an inverse of rate.
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state.counters["foo_inv_rate"] = Counter(
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num_foo, Counter.kIsRate | Counter.kInvert
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)
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# Set a counter as a thread-average quantity.
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state.counters["foo_avg"] = Counter(num_foo, Counter.kAvgThreads)
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# There's also a combined flag:
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state.counters["foo_avg_rate"] = Counter(num_foo, Counter.kAvgThreadsRate)
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@benchmark.register
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@benchmark.option.measure_process_cpu_time()
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@benchmark.option.use_real_time()
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def with_options(state):
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while state:
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sum(range(1_000_000))
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@benchmark.register(name="sum_million_microseconds")
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@benchmark.option.unit(benchmark.kMicrosecond)
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def with_options2(state):
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while state:
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sum(range(1_000_000))
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@benchmark.register
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@benchmark.option.arg(100)
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@benchmark.option.arg(1000)
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def passing_argument(state):
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while state:
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sum(range(state.range(0)))
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@benchmark.register
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@benchmark.option.range(8, limit=8 << 10)
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def using_range(state):
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while state:
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sum(range(state.range(0)))
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@benchmark.register
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@benchmark.option.range_multiplier(2)
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@benchmark.option.range(1 << 10, 1 << 18)
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@benchmark.option.complexity(benchmark.oN)
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def computing_complexity(state):
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while state:
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sum(range(state.range(0)))
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state.complexity_n = state.range(0)
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if __name__ == "__main__":
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benchmark.main()
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