2016-06-02 05:08:01 +08:00
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#undef NDEBUG
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2016-05-19 01:59:34 +08:00
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#include <algorithm>
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2016-10-08 02:04:50 +08:00
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#include <cassert>
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2016-06-04 00:33:17 +08:00
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#include <cmath>
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2016-10-08 02:04:50 +08:00
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#include <cstdlib>
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#include <vector>
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#include "benchmark/benchmark.h"
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#include "output_test.h"
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2016-05-19 01:59:34 +08:00
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2016-06-02 05:08:01 +08:00
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namespace {
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#define ADD_COMPLEXITY_CASES(...) \
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2016-10-08 02:04:50 +08:00
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int CONCAT(dummy, __LINE__) = AddComplexityTest(__VA_ARGS__)
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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int AddComplexityTest(std::string test_name, std::string big_o_test_name,
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std::string rms_test_name, std::string big_o) {
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SetSubstitutions({{"%name", test_name},
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{"%bigo_name", big_o_test_name},
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2016-10-08 02:04:50 +08:00
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{"%rms_name", rms_test_name},
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2016-10-08 11:56:22 +08:00
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{"%bigo_str", "[ ]* %float " + big_o},
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2016-10-08 02:04:50 +08:00
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{"%bigo", big_o},
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{"%rms", "[ ]*[0-9]+ %"}});
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AddCases(
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TC_ConsoleOut,
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{{"^%bigo_name %bigo_str %bigo_str[ ]*$"},
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{"^%bigo_name", MR_Not}, // Assert we we didn't only matched a name.
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{"^%rms_name %rms %rms[ ]*$", MR_Next}});
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AddCases(TC_JSONOut, {{"\"name\": \"%bigo_name\",$"},
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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{"\"run_name\": \"%name\",$", MR_Next},
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Track 'type' of the run - is it an actual measurement, or an aggregate. (#658)
This is *only* exposed in the JSON. Not in CSV, which is deprecated.
This *only* supposed to track these two states.
An additional field could later track which aggregate this is,
specifically (statistic name, rms, bigo, ...)
The motivation is that we already have ReportAggregatesOnly,
but it affects the entire reports, both the display,
and the reporters (json files), which isn't ideal.
It would be very useful to have a 'display aggregates only' option,
both in the library's console reporter, and the python tooling,
This will be especially needed for the 'store separate iterations'.
2018-08-28 23:11:36 +08:00
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{"\"run_type\": \"aggregate\",$", MR_Next},
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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{"\"aggregate_name\": \"BigO\",$", MR_Next},
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Json reporter: don't cast floating-point to int; adjust tooling (#426)
* Json reporter: passthrough fp, don't cast it to int; adjust tooling
Json output format is generally meant for further processing
using some automated tools. Thus, it makes sense not to
intentionally limit the precision of the values contained
in the report.
As it can be seen, FormatKV() for doubles, used %.2f format,
which was meant to preserve at least some of the precision.
However, before that function is ever called, the doubles
were already cast to the integer via RoundDouble()...
This is also the case for console reporter, where it makes
sense because the screen space is limited, and this reporter,
however the CSV reporter does output some( decimal digits.
Thus i can only conclude that the loss of the precision
was not really considered, so i have decided to adjust the
code of the json reporter to output the full fp precision.
There can be several reasons why that is the right thing
to do, the bigger the time_unit used, the greater the
precision loss, so i'd say any sort of further processing
(like e.g. tools/compare_bench.py does) is best done
on the values with most precision.
Also, that cast skewed the data away from zero, which
i think may or may not result in false- positives/negatives
in the output of tools/compare_bench.py
* Json reporter: FormatKV(double): address review note
* tools/gbench/report.py: skip benchmarks with different time units
While it may be useful to teach it to operate on the
measurements with different time units, which is now
possible since floats are stored, and not the integers,
but for now at least doing such a sanity-checking
is better than providing misinformation.
2017-07-25 07:13:55 +08:00
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{"\"cpu_coefficient\": %float,$", MR_Next},
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{"\"real_coefficient\": %float,$", MR_Next},
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2016-10-08 02:04:50 +08:00
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{"\"big_o\": \"%bigo\",$", MR_Next},
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{"\"time_unit\": \"ns\"$", MR_Next},
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{"}", MR_Next},
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{"\"name\": \"%rms_name\",$"},
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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{"\"run_name\": \"%name\",$", MR_Next},
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Track 'type' of the run - is it an actual measurement, or an aggregate. (#658)
This is *only* exposed in the JSON. Not in CSV, which is deprecated.
This *only* supposed to track these two states.
An additional field could later track which aggregate this is,
specifically (statistic name, rms, bigo, ...)
The motivation is that we already have ReportAggregatesOnly,
but it affects the entire reports, both the display,
and the reporters (json files), which isn't ideal.
It would be very useful to have a 'display aggregates only' option,
both in the library's console reporter, and the python tooling,
This will be especially needed for the 'store separate iterations'.
2018-08-28 23:11:36 +08:00
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{"\"run_type\": \"aggregate\",$", MR_Next},
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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{"\"aggregate_name\": \"RMS\",$", MR_Next},
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2016-10-08 12:26:01 +08:00
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{"\"rms\": %float$", MR_Next},
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2016-10-08 02:04:50 +08:00
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{"}", MR_Next}});
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AddCases(TC_CSVOut, {{"^\"%bigo_name\",,%float,%float,%bigo,,,,,$"},
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{"^\"%bigo_name\"", MR_Not},
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{"^\"%rms_name\",,%float,%float,,,,,,$", MR_Next}});
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2016-06-02 05:08:01 +08:00
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return 0;
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}
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} // end namespace
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// ========================================================================= //
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// --------------------------- Testing BigO O(1) --------------------------- //
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// ========================================================================= //
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2016-05-19 01:59:34 +08:00
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void BM_Complexity_O1(benchmark::State& state) {
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2017-10-18 02:17:02 +08:00
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for (auto _ : state) {
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2016-10-08 02:04:50 +08:00
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for (int i = 0; i < 1024; ++i) {
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benchmark::DoNotOptimize(&i);
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}
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2016-05-19 01:59:34 +08:00
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}
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2016-08-05 03:30:14 +08:00
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state.SetComplexityN(state.range(0));
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2016-05-19 01:59:34 +08:00
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}
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2016-10-08 02:04:50 +08:00
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BENCHMARK(BM_Complexity_O1)->Range(1, 1 << 18)->Complexity(benchmark::o1);
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BENCHMARK(BM_Complexity_O1)->Range(1, 1 << 18)->Complexity();
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2018-04-12 22:40:24 +08:00
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BENCHMARK(BM_Complexity_O1)->Range(1, 1 << 18)->Complexity([](int64_t) {
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2016-10-08 02:04:50 +08:00
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return 1.0;
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});
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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const char *one_test_name = "BM_Complexity_O1";
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2016-10-08 02:04:50 +08:00
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const char *big_o_1_test_name = "BM_Complexity_O1_BigO";
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const char *rms_o_1_test_name = "BM_Complexity_O1_RMS";
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const char *enum_big_o_1 = "\\([0-9]+\\)";
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// FIXME: Tolerate both '(1)' and 'lgN' as output when the complexity is auto
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// deduced.
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2016-08-10 04:14:15 +08:00
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// See https://github.com/google/benchmark/issues/272
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2016-10-08 02:04:50 +08:00
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const char *auto_big_o_1 = "(\\([0-9]+\\))|(lgN)";
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const char *lambda_big_o_1 = "f\\(N\\)";
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2016-06-02 05:08:01 +08:00
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// Add enum tests
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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ADD_COMPLEXITY_CASES(one_test_name, big_o_1_test_name, rms_o_1_test_name,
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enum_big_o_1);
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2016-06-02 05:08:01 +08:00
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2016-07-23 07:31:05 +08:00
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// Add auto enum tests
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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ADD_COMPLEXITY_CASES(one_test_name, big_o_1_test_name, rms_o_1_test_name,
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auto_big_o_1);
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2016-07-23 07:31:05 +08:00
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2016-06-02 05:08:01 +08:00
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// Add lambda tests
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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ADD_COMPLEXITY_CASES(one_test_name, big_o_1_test_name, rms_o_1_test_name,
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lambda_big_o_1);
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2016-06-02 05:08:01 +08:00
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// ========================================================================= //
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// --------------------------- Testing BigO O(N) --------------------------- //
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// ========================================================================= //
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2018-04-04 06:12:47 +08:00
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std::vector<int> ConstructRandomVector(int64_t size) {
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2016-06-02 05:08:01 +08:00
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std::vector<int> v;
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2018-04-04 06:12:47 +08:00
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v.reserve(static_cast<int>(size));
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2016-06-02 05:08:01 +08:00
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for (int i = 0; i < size; ++i) {
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2018-07-09 18:45:10 +08:00
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v.push_back(static_cast<int>(std::rand() % size));
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2016-06-02 05:08:01 +08:00
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}
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return v;
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}
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2016-05-19 01:59:34 +08:00
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2016-06-02 05:08:01 +08:00
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void BM_Complexity_O_N(benchmark::State& state) {
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2016-08-05 03:30:14 +08:00
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auto v = ConstructRandomVector(state.range(0));
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2018-04-04 06:12:47 +08:00
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// Test worst case scenario (item not in vector)
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const int64_t item_not_in_vector = state.range(0) * 2;
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2017-10-18 02:17:02 +08:00
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for (auto _ : state) {
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2016-10-08 02:04:50 +08:00
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benchmark::DoNotOptimize(std::find(v.begin(), v.end(), item_not_in_vector));
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2016-05-19 01:59:34 +08:00
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}
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2016-08-05 03:30:14 +08:00
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state.SetComplexityN(state.range(0));
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2016-05-19 01:59:34 +08:00
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}
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2016-10-08 02:04:50 +08:00
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BENCHMARK(BM_Complexity_O_N)
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->RangeMultiplier(2)
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->Range(1 << 10, 1 << 16)
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->Complexity(benchmark::oN);
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BENCHMARK(BM_Complexity_O_N)
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->RangeMultiplier(2)
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->Range(1 << 10, 1 << 16)
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2018-07-09 18:45:10 +08:00
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->Complexity([](int64_t n) -> double { return static_cast<double>(n); });
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2016-10-08 02:04:50 +08:00
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BENCHMARK(BM_Complexity_O_N)
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->RangeMultiplier(2)
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->Range(1 << 10, 1 << 16)
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->Complexity();
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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const char *n_test_name = "BM_Complexity_O_N";
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2016-10-08 02:04:50 +08:00
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const char *big_o_n_test_name = "BM_Complexity_O_N_BigO";
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const char *rms_o_n_test_name = "BM_Complexity_O_N_RMS";
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const char *enum_auto_big_o_n = "N";
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const char *lambda_big_o_n = "f\\(N\\)";
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2016-05-25 04:25:59 +08:00
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2016-06-02 05:08:01 +08:00
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// Add enum tests
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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ADD_COMPLEXITY_CASES(n_test_name, big_o_n_test_name, rms_o_n_test_name,
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enum_auto_big_o_n);
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2016-06-02 05:08:01 +08:00
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// Add lambda tests
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Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
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ADD_COMPLEXITY_CASES(n_test_name, big_o_n_test_name, rms_o_n_test_name,
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lambda_big_o_n);
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2016-06-02 05:08:01 +08:00
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// ========================================================================= //
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// ------------------------- Testing BigO O(N*lgN) ------------------------- //
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// ========================================================================= //
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2016-05-19 01:59:34 +08:00
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static void BM_Complexity_O_N_log_N(benchmark::State& state) {
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2016-08-05 03:30:14 +08:00
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auto v = ConstructRandomVector(state.range(0));
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2017-10-18 02:17:02 +08:00
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for (auto _ : state) {
|
2016-10-08 02:04:50 +08:00
|
|
|
std::sort(v.begin(), v.end());
|
2016-05-19 01:59:34 +08:00
|
|
|
}
|
2016-08-05 03:30:14 +08:00
|
|
|
state.SetComplexityN(state.range(0));
|
2016-05-19 01:59:34 +08:00
|
|
|
}
|
2018-06-05 18:36:26 +08:00
|
|
|
static const double kLog2E = 1.44269504088896340736;
|
2016-10-08 02:04:50 +08:00
|
|
|
BENCHMARK(BM_Complexity_O_N_log_N)
|
|
|
|
->RangeMultiplier(2)
|
|
|
|
->Range(1 << 10, 1 << 16)
|
|
|
|
->Complexity(benchmark::oNLogN);
|
|
|
|
BENCHMARK(BM_Complexity_O_N_log_N)
|
|
|
|
->RangeMultiplier(2)
|
|
|
|
->Range(1 << 10, 1 << 16)
|
2018-07-09 18:45:10 +08:00
|
|
|
->Complexity([](int64_t n) { return kLog2E * n * log(static_cast<double>(n)); });
|
2016-10-08 02:04:50 +08:00
|
|
|
BENCHMARK(BM_Complexity_O_N_log_N)
|
|
|
|
->RangeMultiplier(2)
|
|
|
|
->Range(1 << 10, 1 << 16)
|
|
|
|
->Complexity();
|
|
|
|
|
Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
|
|
|
const char *n_lg_n_test_name = "BM_Complexity_O_N_log_N";
|
2016-10-08 02:04:50 +08:00
|
|
|
const char *big_o_n_lg_n_test_name = "BM_Complexity_O_N_log_N_BigO";
|
|
|
|
const char *rms_o_n_lg_n_test_name = "BM_Complexity_O_N_log_N_RMS";
|
|
|
|
const char *enum_auto_big_o_n_lg_n = "NlgN";
|
|
|
|
const char *lambda_big_o_n_lg_n = "f\\(N\\)";
|
2016-06-02 05:08:01 +08:00
|
|
|
|
|
|
|
// Add enum tests
|
Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
|
|
|
ADD_COMPLEXITY_CASES(n_lg_n_test_name, big_o_n_lg_n_test_name,
|
|
|
|
rms_o_n_lg_n_test_name, enum_auto_big_o_n_lg_n);
|
2016-06-02 05:08:01 +08:00
|
|
|
|
|
|
|
// Add lambda tests
|
Track two more details about runs - the aggregate name, and run name. (#675)
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
2018-09-13 20:08:15 +08:00
|
|
|
ADD_COMPLEXITY_CASES(n_lg_n_test_name, big_o_n_lg_n_test_name,
|
|
|
|
rms_o_n_lg_n_test_name, lambda_big_o_n_lg_n);
|
2016-06-02 05:08:01 +08:00
|
|
|
|
|
|
|
// ========================================================================= //
|
|
|
|
// --------------------------- TEST CASES END ------------------------------ //
|
|
|
|
// ========================================================================= //
|
|
|
|
|
2016-10-08 02:04:50 +08:00
|
|
|
int main(int argc, char *argv[]) { RunOutputTests(argc, argv); }
|