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Increase benchmark iters for Android jobs #6297
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/6297
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit df0db16 with merge base 5e44991 (): This comment was automatically generated by Dr. CI and updates every 15 minutes. |
@huydhn I scheduled 4 runs from different commits, and ensure all 4 runs finished successfully. However, the dashboard only shows 2 commits (expect 4). |
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Expect 4 points from today. Maybe due to the HUD outage |
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@kirklandsign It's a surprise that the total time in Running state varies so much. Take In the 12mins job (seems to be an outlier, maybe due to context switching during execution??), the data is not shown in the dashboard, it's execution latency is 881.29ms, far different from 752.77 and 712.32. 1-3 mins are expected given 752.77ms x 100 / 60000 = 1.25mins for execution and additional 1-2 mins overhead for setup&teardown. |
Good point. I also see something wrong in the log
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That's another issue. All jobs report that actually, for dl3 xnnpack. |
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W/ 1000 iters, still end up having many green|red spots. Since it's still taking less then 10mins, could experiment by bump up iters to 2k |
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Sorry let me fix the app. Probably the run itself is good, but I ran it on UI thread, which we shouldn't. Let me use a background thread for it. Try #6320 |
@@ -42,7 +42,7 @@ protected void onCreate(Bundle savedInstanceState) { | |||
.findFirst() | |||
.get(); | |||
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int numIter = intent.getIntExtra("num_iter", 50); | |||
int numIter = intent.getIntExtra("num_iter", 2000); |
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Honestly when I tried locally I see 100 is already stable :p
Per the test here the data variance from run-to-run are still very large on Android.
Test several runs from different commits:
Metrics Comparison on the dashboard: