[Inductor] [Doc] Add debugging document for inductor cpu backend #2430
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@jgong5 @EikanWang Hi, please review for the draft document of inductor debugging. The part of profiling would be added soon. cc @zhuhaozhe |
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Can you write the tutorial as a |
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@Valentine233 thanks so much for this document. If you'd like to write this as .py, you can use this template. |
| with torch.no_grad(): | ||
| compiled_model(**input_dict) | ||
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| NUM_ITERS=100 |
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@Valentine233 can we reduce this to a reasonable smaller number?
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Hi, @svekars. Thanks for review, I will reduce it.
| inductor_func(*input) | ||
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| import timeit | ||
| NUM_ITERS=1000 |
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@Valentine233 Can we reduce this to a reasonable smaller number?
| # .. code-block:: shell | ||
| # | ||
| # eager use: 5.780875144992024 ms/iter | ||
| # inductor use: 0.9588955780491233 ms/iter | ||
| # speed up ratio: 6.0286805751604735 | ||
| # |
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This will be generated in the final [HTML]( I see duplicate outputs in the resulting HTML: https://docs-preview.pytorch.org/pytorch/tutorials/2430/intermediate/inductor_debug_cpu.html#performance-profiling ). Can we remove this block or state in which env you get this numbers if it's important to show specifically these results?
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Hi, @svekars. Will this automatically generate results running from time to time and get different outputs? Or will it be frozen after PR is merged?
| # ------------------------- ------------ ------------ ------------ ------------ | ||
| # Name CPU total % CPU total CPU time avg # of Calls | ||
| # ------------------------- ------------ ------------ ------------ ------------ | ||
| # aten::addmm 45.73% 370.814ms 1.024ms 362 | ||
| # aten::add 19.89% 161.276ms 444.287us 363 | ||
| # aten::copy_ 14.97% 121.416ms 248.803us 488 | ||
| # aten::mul 9.02% 73.154ms 377.082us 194 | ||
| # aten::clamp_min 8.81% 71.444ms 744.208us 96 | ||
| # aten::bmm 5.46% 44.258ms 922.042us 48 | ||
| # ProfilerStep* 100.00% 810.920ms 810.920ms 1 | ||
| # aten::div 2.89% 23.447ms 976.958us 24 | ||
| # aten::_softmax 1.00% 8.087ms 336.958us 24 | ||
| # aten::linear 46.48% 376.888ms 1.041ms 362 | ||
| # aten::clone 2.77% 22.430ms 228.878us 98 | ||
| # aten::t 0.31% 2.502ms 6.912us 362 | ||
| # aten::view 0.14% 1.161ms 1.366us 850 | ||
| # aten::transpose 0.17% 1.377ms 3.567us 386 | ||
| # aten::index_select 0.12% 952.000us 317.333us 3 | ||
| # aten::expand 0.12% 986.000us 2.153us 458 | ||
| # aten::matmul 8.31% 67.420ms 1.405ms 48 | ||
| # aten::cat 0.09% 703.000us 703.000us 1 | ||
| # aten::as_strided 0.08% 656.000us 0.681us 963 | ||
| # aten::relu 8.86% 71.864ms 748.583us 96 | ||
| # ------------------------- ------------ ------------ ------------ ------------ | ||
| # Self CPU time total: 810.920ms | ||
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| ###################################################################### | ||
| # | ||
| # Similarly, we also get the table for the compiled model with Inductor (omitting some columns): | ||
| # |
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This will be generated in the final [HTML]( I see duplicate outputs in the resulting HTML: https://docs-preview.pytorch.org/pytorch/tutorials/2430/intermediate/inductor_debug_cpu.html#performance-profiling ). Can we remove this block or state in which env you get this numbers if it's important to show specifically these results?
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Hi, @svekars. The generated table is not in good format ( It's too long for 1 line).
For all output related blocks, can we choose the comment out print and use our results ( with env setting and system types)?
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yes, I think it is fine. Or we can keep both and say something like this before the not generated output: The following output was generated on .... hardware.
…233/tutorials into add_inductor_debug_doc
| # numactl -C 0-31 -m 0 python bench.py | ||
| # | ||
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| # bench.py |
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| # bench.py | |
| # Code for ``bench.py``: |
Fixes #2348
Description
The doc is intended to introduce the usage, debugging and performance profiling for
torch.compilewith Inductor CPU backend.Checklist
cc @williamwen42 @msaroufim @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @ZailiWang @ZhaoqiongZ @leslie-fang-intel @Xia-Weiwen @sekahler2 @CaoE @zhuhaozhe