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Update example commands in README
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README.md

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@@ -44,22 +44,34 @@ conda env create -n rapids --solver=libmamba -f envs/conda-env-rapids.yml
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### Benchmarks Runner
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How to run benchmarks using the `sklbench` module and a specific configuration:
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How to run sklearnex benchmarks on CPU using the `sklbench` module and regular scope of benchmarking cases:
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```bash
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python -m sklbench --config configs/sklearn_example.json
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python -m sklbench --configs configs/regular \
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--filters algorithm:library=sklearnex algorithm:device=cpu \
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--environment-name ENV_NAME --result-file result_sklearnex_cpu_regular.json
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# same command with shorter argument aliases for typing convenience
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python -m sklbench -c configs/regular \
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-f algorithm:library=sklearnex algorithm:device=cpu \
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-e ENV_NAME -r result_sklearnex_cpu_regular.json
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```
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The default output is a file with JSON-formatted results of benchmarking cases. To generate a better human-readable report, use the following command:
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```bash
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python -m sklbench --config configs/sklearn_example.json --report
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python -m sklbench -c configs/regular \
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-f algorithm:library=sklearnex algorithm:device=cpu \
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-e ENV_NAME -r result_sklearnex_cpu_regular.json \
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--report --report-file result-sklearnex-cpu-regular.xlsx
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```
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By default, output and report file paths are `result.json` and `report.xlsx`. To specify custom file paths, run:
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In order to optimize datasets downloading and get more verbose output, use `--prefetch-datasets` and `-l INFO` arguments:
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```bash
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python -m sklbench --config configs/sklearn_example.json --report --result-file result_example.json --report-file report_example.xlsx
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python -m sklbench -c configs/regular \
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-f algorithm:library=sklearnex algorithm:device=cpu \
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-e ENV_NAME -r result_sklearnex_cpu_regular.json \
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--report --report-file report-sklearnex-cpu-regular.xlsx \
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--prefetch-datasets -l INFO
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```
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For a description of all benchmarks runner arguments, refer to [documentation](sklbench/runner/README.md#arguments).
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To combine raw result files gathered from different environments, call the report generator:
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```bash
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python -m sklbench.report --result-files result_1.json result_2.json --report-file report_example.xlsx
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python -m sklbench.report \
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--result-files result_1.json result_2.json \
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--report-file report_example.xlsx
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```
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For a description of all report generator arguments, refer to [documentation](sklbench/report/README.md#arguments).

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