dmlc--dgl
Minjie Wang
30 行
1.3 KiB
Markdown
30 行
1.3 KiB
Markdown
How to add test to regression
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Official link to [asv](https://asv.readthedocs.io/en/stable/writing_benchmarks.html)
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## Add test
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DGL reuses the ci docker image for the regression test. There are four conda envs, base, mxnet-ci, pytorch-ci, and tensorflow-ci.
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The basic use is execute a script, and get the needed results out of the printed results.
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- Create a new file in the tests/regression/
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- Follow the example `bench_gcn.py` or the [official instruction](https://asv.readthedocs.io/en/stable/writing_benchmarks.html)
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- function name starts with `track` will be used to generate the stats, by the return value
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- setup function would be execute every time before running track function
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- Can use params to pass parameter into `setup` and `track_` functions
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## Run locally
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```bash
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docker run --name dgl-reg --rm --hostname=reg-machine --runtime=nvidia -dit dgllib/dgl-ci-gpu:conda /bin/bash
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docker cp /home/ubuntu/asv_data dgl-reg:/root/asv_data/
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docker exec dgl-reg bash /root/asv_data/run.sh
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docker cp dgl-reg:/root/regression/dgl/asv/. /home/ubuntu/asv_data/ # Change /home/ubuntu/asv to the path you want to put the result
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docker stop dgl-reg
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```
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And in the directory you choose (such as `/home/ubuntu/asv_data`), there's a `html` directory. You can use `python -m http.server` to start a server to see the result
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