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for 2 trials, each of them lasting for 30 minutes, but it hasn’t finished generating report data. Running the same command and configuration in the local experiment already terminated.
It seems like the processes are sleeping for the majority of time. htop output also shows that measuring processes are getting scheduled, but there’s less than 1% usage of CPU for each scheduled process.
Is there any solution to make it generate report faster?
run_experiment script also steadily outputs this warning in case it is relevant.
/usr/local/lib/python3.10/site-packages/jinja2/runtime.py:298: FutureWarning: this method is deprecated in favour of `Styler.to_html()`
return __obj(*args, **kwargs)
/work/src/analysis/plotting.py:159: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 95)` for the same effect.
axes = sns.lineplot(
/work/src/analysis/plotting.py:159: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 95)` for the same effect.
axes = sns.lineplot(
/usr/local/lib/python3.10/site-packages/seaborn/matrix.py:202: RuntimeWarning: All-NaN slice encountered
vmin = np.nanmin(calc_data)
/usr/local/lib/python3.10/site-packages/seaborn/matrix.py:207: RuntimeWarning: All-NaN slice encountered
vmax = np.nanmax(calc_data)
in the loop DEBUG
/usr/local/lib/python3.10/site-packages/jinja2/runtime.py:298: FutureWarning: this method is deprecated in favour of `Styler.to_html()`
return __obj(*args, **kwargs)
/work/src/analysis/plotting.py:159: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 95)` for the same effect.
axes = sns.lineplot(
/work/src/analysis/plotting.py:159: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 95)` for the same effect.
axes = sns.lineplot(
/usr/local/lib/python3.10/site-packages/seaborn/matrix.py:202: RuntimeWarning: All-NaN slice encountered
vmin = np.nanmin(calc_data)
/usr/local/lib/python3.10/site-packages/seaborn/matrix.py:207: RuntimeWarning: All-NaN slice encountered
vmax = np.nanmax(calc_data)
The text was updated successfully, but these errors were encountered:
I also found that FuzzBench does more stuff when running on GCP, which makes it less robust. I cannot see logs from screen but have to visit GCP console to see log reporting, but I still cannot find the reason why FuzzBench stops working on GCP.
(I failed to run FuzzBench by setting a GCP project due to the error in #1911, so I am actually running local experiment on GCP VM instances)
It seems like
run_experiment
in GCP takes longer to generate a report. It has been more than 5+ hours since I started executing following command:for 2 trials, each of them lasting for 30 minutes, but it hasn’t finished generating report data. Running the same command and configuration in the local experiment already terminated.
The
run_experiment
is looping in this loop:fuzzbench/experiment/dispatcher.py
Line 166 in ba22647
It seems like the processes are sleeping for the majority of time.
htop
output also shows that measuring processes are getting scheduled, but there’s less than 1% usage of CPU for each scheduled process.Is there any solution to make it generate report faster?
run_experiment
script also steadily outputs this warning in case it is relevant.The text was updated successfully, but these errors were encountered: