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In benchmarking only mode, sometimes we actually do want to use grid search to evaluate all possibilities for comparison sake.
This can also be useful when comparing more efficient optimizer search strategy performance as well.
We should be able to implement this as an additional mlos_bench optimizer in combination with the storage backend to check which ones have already been evaluated.
The text was updated successfully, but these errors were encountered:
Closes#688
- Introduces `GridSearchOptimizer` to `mlos_bench`
- Generates and stores a set of `tuple(dict.values())` from
`ConfigSpace` to track elements of the config grid to search
- If `max_iterations` > `len(grid)` can refill the grid if desired
(e.g., by calling `suggest()` after `not_converged()` returns `False`.
- If `max_iterations` < `len(grid)` (i.e., we don't have enough
iterations to complete the grid) will issue a warning.
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Co-authored-by: Sergiy Matusevych <sergiym@microsoft.com>
Co-authored-by: Sergiy Matusevych <sergiy.matusevych@gmail.com>
In benchmarking only mode, sometimes we actually do want to use grid search to evaluate all possibilities for comparison sake.
This can also be useful when comparing more efficient optimizer search strategy performance as well.
We should be able to implement this as an additional mlos_bench optimizer in combination with the storage backend to check which ones have already been evaluated.
The text was updated successfully, but these errors were encountered: