Added support for plot #2825
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Added support for plot #2825
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Signed-off-by: Alexandre Eichenberger <[email protected]>
Signed-off-by: Alexandre Eichenberger <[email protected]>
cjvolzka
approved these changes
May 14, 2024
utils/make-report.py
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| Parameters to focus analysis: | ||
| -f/--focus <regexp>: Focus only on ops that match the regexp pattern. | ||
| -m/--min <num>: Focus on operations with at least <num>% of exec time. | ||
| -supported: Focus only on ops that are supported. Namely, the report |
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nit: Typo, should be --supported:
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nice catch, thanks
Signed-off-by: Alexandre Eichenberger <[email protected]>
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Jenkins Linux amd64 Build #14825 [push] Added support for plot (... started at 13:40 |
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Jenkins Linux s390x Build #14830 [push] Added support for plot (... started at 14:40 |
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Jenkins Linux ppc64le Build #13855 [push] Added support for plot (... started at 14:53 |
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Jenkins Linux amd64 Build #14825 [push] Added support for plot (... passed after 1 hr 3 min |
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Jenkins Linux s390x Build #14830 [push] Added support for plot (... passed after 1 hr 28 min |
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Jenkins Linux ppc64le Build #13855 [push] Added support for plot (... passed after 1 hr 56 min |
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Added the possibility to generate a jpg with the plot of the result of the analysis of a run.
Recall how to gather data of a run (here run Roberta, gather compile time info on parallel (
-opt-report=Parallel, saved with--log-to-file compile.log) and runtime info (--profile-ir=ZHighsaved withONNX_MLIR_INSTRUMENT_FILE=run.log).ONNX_MLIR_INSTRUMENT_FILE=run.log RunONNXModel.py -m roberta-base-11.onnx -c "-O3 -mcpu=z16 -maccel=NNPA -parallel -opt-report=Parallel --profile-ir=ZHigh" --shape-info=0:6x384 --log-to-file compile.log -w 3 -n 16Then you may view and print statistics as follow
python3 ~/OM/onnx-mlir/utils/make-report.py -ums -r run.log -w 3 -p output -umswhere the raw data is taken from a run-file named
run.logskipping the first 3 warmup runs (-w 3) with output in miliseconds (-umsfor unit in ms). The resulting graph is:Say you would like to focus the results on operations that take at least 1% of execution time, and report the ops in alphabetical order (default is by decreasing order of execution time). Add the
-m 1 --sort nameand you get this graphSay you now want to correlate the runtime info with statistics of operations that ran in parallel or not. Update the command to provide the compile-time log:
python3 ~/OM/onnx-mlir/utils/make-report.py -ums -r run.log -c compile.log -s par -p output -m 1 --sort name