Update example commands in README #182
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| By default, output and report file paths are `result.json` and `report.xlsx`. To specify custom file paths, run: | ||
| In order to optimize datasets downloading and get more verbose output, use `--prefetch-datasets` and `-l INFO` arguments: |
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Please remember to provide info about the requirements for kaggle data.
| # Same command with shorter argument aliases for typing convenience | ||
| python -m sklbench -c configs/regular \ | ||
| -f algorithm:library=sklearnex algorithm:device=cpu \ | ||
| -e ENV_NAME -r result_sklearnex_cpu_regular.json |
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This ENV_NAME is very unclear to me.
The docs say:
Environment name to use instead of it's configuration hash.
But that doesn't tell me what the environment is or what is is used for. Should ENV_NAME be substituted with something else? Is it required?
| @@ -69,7 +88,9 @@ For a description of all benchmarks runner arguments, refer to [documentation](s | |||
| To combine raw result files gathered from different environments, call the report generator: | |||
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| ```bash | |||
| python -m sklbench.report --result-files result_1.json result_2.json --report-file report_example.xlsx | |||
| python -m sklbench.report \ | |||
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I think this one is missing the flag that's needed when mixing sklearn and sklearnex.
| ```bash | ||
| python -m sklbench --config configs/sklearn_example.json --report --result-file result_example.json --report-file report_example.xlsx | ||
| # ... | ||
| -f algorithm:library=sklearnex algorithm:device=cpu algorithm:estimator=PCA,KMeans |
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Here it could mention that these algorithms need to be in the config JSON.
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| To select measurement for few algorithms only, extend filter (`-f`) argument: |
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| To select measurement for few algorithms only, extend filter (`-f`) argument: | |
| To run benchmarks for a for few algorithms only, extend filter (`-f`) argument: |
| ``` | ||
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| By default, output and report file paths are `result.json` and `report.xlsx`. To specify custom file paths, run: | ||
| In order to optimize datasets downloading and get more verbose output, use `--prefetch-datasets` and `-l INFO` arguments: |
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Why not to use --prefetch-datasets as the default recommendation for regular runs?
Does it have any drawbacks?
Description
PR should start as a draft, then move to ready for review state after CI is passed and all applicable checkboxes are closed.
This approach ensures that reviewers don't spend extra time asking for regular requirements.
You can remove a checkbox as not applicable only if it doesn't relate to this PR in any way.
Checklist to comply with before moving PR from draft:
PR completeness and readability
Testing