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AVHopp
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Like the way this is going! Have some more ideas for further simplification
AVHopp
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Some comments related to parts of the design that I still do not fully agree with resp. understand
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@Hrovatin any movement in this PR or should we close it? |
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@Scienfitz still on my todo list to add your last two comments |
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Updated the docstring to clarify that the callable now shifts both dimensions and bounds for the Hartmann function.
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Scienfitz
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lgtm, last comments but otherwise ready for merge
| # They are anyway only set for 3D and 6D hartman in the parent class | ||
| if self._optimizers is not None: | ||
| self._optimizers = None | ||
| self.optimizers = None |
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.optimizers might be a property that you cant just overwrite, please check
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This works from the code perspective - what do you mean by checking it @Scienfitz ?
h=ShiftedHartmann([0,0.1,1],dim=3)
print(h.optimizers,h._optimizers)
None None
They are only used in some botorch testing utils
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I think optimizers is a @property, so you shouldnt just overwrite it because properties are read-only
this is not (just) my opinion, mypy says the same, currently blocking your PR in CI
Imo there is a high chance that .optimizers just returns the value of ._optimizers + performs some checks
I did not check this myself, so you should
- "check" in the botorch code whether
optimizersis really a property and is related to_optimizersthe way I suspect - you could comment out your
.optimizersassignment line, instantiate your custm class and call the objects.optimizersand check that it coincides with your assigned._optimizers
I suspect that removing the .optimizers line already does the job (not sure whether there is more mypy complains about, please check as well and always run or instruct your agent to run tox -e mypy-py310)
AVHopp
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LGTM, only one general question and need a bit more time before I can approve
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Some minor comments on the docstrings and type hints. Other than that, everything is either flagged by the CI (type error in mypy) or opened as a comment.
Add two new TL benchmarks:
@kalama-ai