Comments (26)
Sorry @pusolito I had no time to look into it. I will try to have a look by the end of the month (do not hesitate to ping me).
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I honestly do not remember of the top of my head. I think the concern here is that this kind of indirection increase the system to solve size and could lead to bad performance if abused, which is also a valid concern for required edit variables. If we allow it we have to be clear about the trade-off in the documentation.
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Thanks for the quick reply! đ
In my case, I need to update the edit variables whenever an object "tries" to adjust. I could discard the solver each time, but I'm hoping to gain a bit of speed by keeping it around and not rebuilding the constraints each time something adjusts. I also see the same growth for any equals
constraint actually. So this is independent of edit variables. I just happened to notice it there b/c mine contained equality constraints.
Do you have recommendations for how to do the cleanup correctly? I am actually working with a port of this lib that I have full code control over.
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The case for a single equals
constraint is that 2 Error
entries are added to the objective, but only 1 is removed when that constraint is remove.
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Interesting. Thanks for clarifying. As you suggested, I'll follow up with more context on my use case to get more guidance.
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So the leak was actually a bug in the port. But I'll provide more details of my use case still since I'm trying to improve performance while doing more dynamic updates to the constrains/edits.
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Ok, I know it's been a while. But I made a lot of good progress on optimizing my solution in the general cases. Now I'm thinking about a slightly different problem. The implementation is very efficient when updating variables, which makes sense. But I have cases where it would be great to express the idea of a "read-only" variable. This would work great in UI layout cases, where you'd like to have a relationship with a parent element that is dynamic, as in it can change over time, yet the solver never tries to update it unless you explicitly suggest a value for it. So essentially, "read-only" edit variables.
And example of this would be: child.left + child.width == parent.width / 2
where you want to avoid the solver ever changing parent.width
, but you want the ability to set/suggest it over time.
Right now I solve this by removing constraints and re-adding them as follows, but this is inefficient.
+ `child.left + child.width == 100
- `child.left + child.width == 100
+ `child.left + child.width == 200
Any suggestions for how you might address this or evolve the solver to handle it?
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As suggested @sccolbert in one of his earlier comment you could use an edit variable with a required strength. As a consequence the solver won't change it but you will be able to.
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Edit variables can't actually have a strength of required:
Line 211 in 78134f7
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I wondered about that, and would be interested in using that ability if possible. Separately, I am exploring a method like suggestValue that updates the constant for a constraint. So far this seems to work.
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Maybe we can experiment with removing that restriction.
That would be incredible.
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I think this was forbidden because if abused it can easily lead to poor performance. @sccolbert any memory of why you forbid it.
Lifting the restriction in itself would be easy but would call for some extra documentation on when it should be used. Would anybody be interested in making a PR ?
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As mentioned, I created a new method for updating a constraint. It looks basically like this (though I'm working in Kotlin, so apologize if the port isn't quite right):
void updateConstant( const Constraint& old, const Constraint& new )
{
auto cn_it = m_cns.find( old );
if( cn_it == m_cns.end() )
throw UnknownConstraint( old );
DualOptimizeGuard guard( *this );
Tag tag( cn_it->second );
m_cns.erase( cn_it );
m_cns[ new ] = tag;
double delta = new.expression.constant - old.expression.constant
// Check first if the positive error variable is basic.
auto row_it = m_rows.find( tag.marker );
if( row_it != m_rows.end() )
{
if( row_it->second->add( -delta ) < 0.0 )
m_infeasible_rows.push_back( row_it->first );
return;
}
// Check next if the negative error variable is basic.
row_it = m_rows.find( tag.other );
if( row_it != m_rows.end() )
{
if( row_it->second->add( delta ) < 0.0 )
m_infeasible_rows.push_back( row_it->first );
return;
}
// Otherwise update each row where the error variables exist.
for (const auto & rowPair : m_rows)
{
double coeff = rowPair.second->coefficientFor( tag.marker );
if( coeff != 0.0 &&
rowPair.second->add( delta * coeff ) < 0.0 &&
rowPair.first.type() != Symbol::External )
m_infeasible_rows.push_back( rowPair.first );
}
}
This seems to work fine for constraints with required
strength, but if doesn't have the desired result for those with lower strength. Any suggestions? My assumption was that this would work generally given that suggestValue
does a similar thing.
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Any suggestion for what could be wrong with the approach above?
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Looking at what you are doing I am confused by the fact that you pass a new constraint instead of simply a new constant value. In particular you fully remove the old constraints and add the new which seems at odd with your intent. Did you try simply updating the constant without removing/adding constraints ?
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The reason for this is that I'm tracking the list of constraints outside of the Solver for a layout manager. Those constraints are checked for changes whenever the UI layouts need to be recalculated. I then do a diff and add/remove/update any constraints that have changed. This means I need to Solver's internal map of constraints to reflect what is tracked outside. Updating the row directly w/o removing the old constraint and adding the new one would mean the Solver throws unknown constraint errors when subsequent calls come in related to the new constraint.
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I am confused because this deviates from your original use case which was about modifying the constant of a constraint. Here you are attempting to fully remove a constraint which, as @sccolbert has described earlier in this thread, is expensive and I don't think your are fully cleaning it up in your current code.
Why is updating a constraint constant not sufficient anymore ?
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This is not really different than my original use case. I still essentially want to modify the constant of a constraint. But it is more complex than that. I'm using the Solver as a part of a larger constraint layout manager. You can see more in this project (repo).
In my case, the layout manager recomputes constraints (actually regenerates them) whenever part of the UI needs recomposition (i.e. something moves or resizes). This means I have a list of brand new constraint instances and need to diff them against the previous tracked list. Upon finding a difference, I update the Solver. This sometimes means removing or adding new constraints.
My use case is trying to speed up the instances when the difference in a constraint is simply a constant value. I'd like to just update the constraint in this case. But, I still need to have the Solver reflect the new constraint after the update, so that subsequent operations on the Solver don't fail with constraint unknown.
For example, let's say you setup the following constraints in my framework. The parent.width
and parent.right
resolve to constant values since parent properties in constraints are non-modifiable by default.
layout = constrain(view1, view2) { v1, v2 ->
v1.width eq parent.width
v2.right eq parent.right - 10
}
However, this block is re-evaluated every time the parent width
ore height
changes. So the underlying manger will see its constraint list change each time. It then does a diff to see if anything has been added/deleted/updated (these blocks can have conditional logic since they are just lambdas, etc.). In this case, it will see that 2 constraints have been deleted and 2 added. But, the changes can also be seen to differ only by constants.
This is the case where I'd like to modify the internal Solver constrain constants instead of doing an expensive remove then add. However, I still currently need the Solver to be left with constraints that reflect the latest state. That is, the new constraints (which are not equivalent to the former ones) are assumed in the Solver once the manager is done with a pass.
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Thanks for the detailed explanation.
Looking at it this way, to me at least, it looks like convincing your manager that the latest built constraint is not always the relevant one may be easier. Since you diff anyway, couldn't you determine the relevant constraints from the diff result.
One thing that bugs me though is that an edit variable is basically a constraint with an == and a strength. Out of curiosity when you say your function does not work for strength that are not required, is it for == constraint or <= and >= ? If the later case we could try to dig deeper since this is a case that does not exist for edit variables.
BTW I am still open to allowing required variable edits if that helps (but in this case I doubt it)
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BTW I am still open to allowing required variable edits if that helps (but in this case I doubt it)
Not to derail the conversation too much, but isn't it the case that some_var == 10
is also discouraged? Wouldn't required variable edits speed things up?
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@MatthieuDartiailh, I think the issue shows up whenever I have a constraint with a strength less than required. So I don't think it matters if the constraint is ==, <=, or >=. But I'll confirm.
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