Add measurements framework (#789)#789
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Summary: Add a measurements framework that evaluates different compression methods by running multiple strategies (ML selector, best-successor per cluster, brute-force per sample, generic ML, plain zstd) on captured sample data and printing a side-by-side comparison table. Added test cases for the measurements and python integration so managed compression trainer can trigger measurements if --capture-data is specified Differential Revision: D106423347
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Summary: Add a measurements framework that evaluates different compression methods by running multiple strategies (ML selector, best-successor per cluster, brute-force per sample, generic ML, plain zstd) on captured sample data and printing a side-by-side comparison table. Added test cases for the measurements and python integration so managed compression trainer can trigger measurements if --capture-data is specified Differential Revision: D106423347
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Summary: Add a measurements framework that evaluates different compression methods by running multiple strategies (ML selector, best-successor per cluster, brute-force per sample, generic ML, plain zstd) on captured sample data and printing a side-by-side comparison table. Added test cases for the measurements and python integration so managed compression trainer can trigger measurements if --capture-data is specified Differential Revision: D106423347
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Summary:
Add a measurements framework that evaluates different compression methods by running multiple strategies (ML selector, best-successor per cluster, brute-force per sample, generic ML, plain zstd) on captured sample data and printing a side-by-side comparison table.
Added test cases for the measurements and python integration so managed compression trainer can trigger measurements if --capture-data is specified
Differential Revision: D106423347