UxperfParser class is moved from the UxperfResultProcessor class into a new
python module in utils. This will help to use the UxperfParser even when
the result procesor is not configured.
Log time changed to produce epoch time in milli seconds.
Nano to milli second conversion done in uxperf result
processor is removed.
Tested on Mate8 and time obtained is verified.
The uxperf result processor now provides warnings for unmatched UX_PERF
markers when running the fps instrument. Previously unmatched markers
resulted in an exception being thrown. Includes additional logging for
debugging purposes.
- Implement a new Marker API in BaseUiAutomation so workload can
generate start and end markers with string name. Outputs to logcat.
- Document the Marker output log format in the WA documentation
- Create a results processor to take existing instrument fps logs and
parse them based on the workload markers. Produce per-action fps
metrics.
- Add simple timing results based on the workload markers
cpustates can now handle the lack of a start marker in three ways:
- try: If the start marker is present only the correct section of the trace
will be used, if its not the whole trace will be used.
- error: An error will be raised if the start marker is missing
- ignore: The markers are ignored and the whole trace is always used.
Before WA would raise a error message that wasn't very clear.
Now when cpustates tries to nudge cores and and error occurs it
will only show a warning (which promts users to check if the cpu is
hot plugged out) and keep going with the reset of the run without
causing errors in other WA extensions.
Previously, only reports that were generated were returned. With this
commit, there will be an entry for each active reporter in the returned
list. If a reporter did not produce a valid report, the entry will be
None.
This ensures consistent output, even if a run time issue causes a
reporter not to produce a report (e.g. if cpufreq events were not
enabled).
It is not possible to read frequencies from a core that has been hotplugged.
The code will now set the current and max frequencies of hotplugged cores
to None.
This still doesn't work for devices that have dynamic hotplug enabled
Fixed error in percentage when frequency is 'None'. Now default to 0 in these cases
cpu_utilisation is now a separate parameter in cpustate. Now generates a floating point number representing the utilisation based on the maximum frequency of the capture. No longer performs averaging of values, this can be done as a post-processing step
cpu utilisation now based on the max cpu freq per core, not max captured freq overall
cpustate result processor generates a view of the cpu subsystem power
state during execution of a workload from cpu_idle and cpu_frequency
ftraces. There exists a period before the first events in those
categories are seen where the state of the cpu subsystem is (partially)
unknown and it is reported as such by the result processor.
Unknown state usually exists for a relatively short period of time and
is generally not a big deal. For certain kinds of workloads, however, it
may constitude a significant protion of the trace.
Changes in this commit attempt to deal with this by a) reading starting
cpu frequencies and writing them into the trace, and b) nudging each
core to bring it out of idle; this happens before the start marker, so
that the system state between the markers should be completely known.
If the value of a classifier was zero (or any other value that
interprets as boolean False), it used to be coverted to an empty entry.
This makes sure that the value gets correctly ropagated.
Adding global aliases to parameters to fix old configs that still used
the deprecated "<ext name>_<param name>" format for specifying parameter
values.
- add IterationResult-level classifiers that get merged into every
added metric (saves having to pass the same classifiers to each
metric added).
- Added a global alias to csv result processor's use_all_classifiers
attribute.
- Adding "classifiers" field to Metric objects. This is a dict mapping
classifier names (arbitrary strings) to corresponding values for that
specific metrics. This is to allow extensions to add
extension-specific annotations to metric that could be handled in a
generic way (e.g. by result processors).
- Updating telemetry workload to add classifiers for the url and internal
iteration (or "time") for a particular result.
- Updating csv result processor with the option to use classifiers to
add columns to results.csv (either using all classifiers found, or
only for the specific ones listed).
cpuidle module implements cpuidle state discovery, query and
manipulation for a Linux device. This replaces the more primitive
get_cpuidle_states method of LinuxDevice.
Renamed APIs (and added a couple of new ones) to be more consistent:
"core" APIs take a core name as the parameter (e.g. "a15") or whatever
is listed in core_names for that device.
"cluster" APIs take a numeric cluster ID (eg. 0) as the parameter. These
get mapped using core_clusters for that device.
"cpu" APIs take a cpufreq cpu ID as a parameter. These could be
integers, e.g. 0, or full string id, e.g. "cpu0".
The internal ABI for ipython has changed between ipython version 2 and
3. In its current state, the result processor only works with IPython
version 2, so fail if the user wants to use the result processor with
the wrong version.
Abstract the ipython interface to a file so that we can make it support
versions 2 and 3 at the same time.
This result processor displays a desktop notification when the run
finishes. It's useful when you are running a long agenda in WA and want
to be notified when the results are available.
