New KNITRO direct solver interface #3707
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eminyouskn
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Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## main #3707 +/- ##
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- Coverage 89.18% 89.16% -0.03%
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Files 896 906 +10
Lines 103725 104488 +763
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+ Hits 92508 93166 +658
- Misses 11217 11322 +105
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Hi @eminyouskn - okay, so, the tests are running but a large number of them are failing. Here is part of the stacktrace: Most of the failures are just tolerance problems / the tolerance needs to be loosened. |
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One-off failures: Second one-off: |
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Thanks @mrmundt for the report. I didn’t run these tests locally since I didn’t have NumPy installed, and in that case, the tests are skipped. I’ll make sure to check them before pushing code from now on. I do have a question: is there a way to adjust the tolerance for all these tests at once? Ideally, we’d only change it for Knitro, but I imagine that might be more complicated. Regarding the two remaining failures, I’ve already fixed the one related to the objective. However, I’m not sure how to address the stale one, it’s not clear to me what exactly that test is supposed to check. |
Co-authored-by: Miranda Mundt <[email protected]>
mrmundt
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Sep 30, 2025
jsiirola
reviewed
Oct 7, 2025
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We want this in today's release, so we are going to merge it. However, we think there are some lingering opportunities for improvement that we'd like to address with a future PR. Thanks, @eminyouskn ! |
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jsiirola
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Oct 17, 2025
| ConfigValue( | ||
| domain=Bool, | ||
| default=False, | ||
| doc="KNITRO solver does not allow variable removal. We can either make the variable a continuous free variable or rebuild the whole model when variable removal is attempted. When `rebuild_model_on_remove_var` is set to True, the model will be rebuilt.", |
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It would be good to split this into multiple strings to keep line lengths <= 88 characters
| ConfigValue( | ||
| domain=Bool, | ||
| default=False, | ||
| doc="To evaluate non-linear constraints, KNITRO solver sets explicit values on variables. This option controls whether to restore the original variable values after solving.", |
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It would be good to split this into multiple strings to keep line lengths <= 88 characters
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| if item.has_lb(): | ||
| bounds_map[BoundType.LO][i] = value(item.lb) | ||
| if item.has_ub(): | ||
| bounds_map[BoundType.UP][i] = value(item.ub) |
There was a problem hiding this comment.
It would be more efficient to do:
Suggested change
| if item.has_lb(): | |
| bounds_map[BoundType.LO][i] = value(item.lb) | |
| if item.has_ub(): | |
| bounds_map[BoundType.UP][i] = value(item.ub) | |
| lb, ub = item.bounds | |
| if lb is not None: | |
| bounds_map[BoundType.LO][i] = lb | |
| if ub is not None: | |
| bounds_map[BoundType.UP][i] = ub |
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| if item.equality: | ||
| bounds_map[BoundType.EQ][i] = value(item.lower) | ||
| continue | ||
| if item.has_lb(): | ||
| bounds_map[BoundType.LO][i] = value(item.lower) | ||
| if item.has_ub(): | ||
| bounds_map[BoundType.UP][i] = value(item.upper) |
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(Note: .lower returns an expression, .lb returns the value)
Also, it is more efficient to retrieve the bounds at once:
Suggested change
| if item.equality: | |
| bounds_map[BoundType.EQ][i] = value(item.lower) | |
| continue | |
| if item.has_lb(): | |
| bounds_map[BoundType.LO][i] = value(item.lower) | |
| if item.has_ub(): | |
| bounds_map[BoundType.UP][i] = value(item.upper) | |
| lb, body, ub = item.to_bounded_expression(evaluate_bounds=True) | |
| if item.equality: | |
| bounds_map[BoundType.EQ][i] = lb | |
| continue | |
| if lb is not None: | |
| bounds_map[BoundType.LO][i] = lb | |
| if ub is not None: | |
| bounds_map[BoundType.UP][i] = ub |
| return knitro.KN_set_double_param | ||
| elif param_type == knitro.KN_PARAMTYPE_STRING: | ||
| return knitro.KN_set_char_param | ||
| raise DeveloperError() |
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This is great defensive programming, but it would be good for these exceptions to have informative messages to help us track things down if they are ever reported.
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| """ | ||
| generator = block.component_data_objects( | ||
| Constraint, descend_into=True, active=True, sort=True |
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It will be significantly more efficient to not use sort=True and instead use sort=SortComponents.deterministic
| This method computes the gradient of the expression with respect to all | ||
| variables and stores the results in the grad attribute. | ||
| """ | ||
| derivative = reverse_sd(self.func_expr) |
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TODO: we should evaluate the computational performance of native python symbolic derivatives. Some alternatives:
- compile the expressions into executable python code (to avoud needing to use the Pyomo expression evaluator
- use AD instead of SD (particularly the APPSI c-extension?)
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Fixes NA
Summary/Motivation:
This PR introduced a new KNITRO direct solver interface.
Changes proposed in this PR:
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