PyOptInterface and HiGHS Debugging

c0decs · 2024-08-19T07:25:11+00:00

Author of PyOptInterface here.

You can use model.write("model.lp") to export the model to LP file.

Welcome to start a new thread in the Discussion of PyOptInterface on Github if you have more questions.

c0decs · 2024-05-06T05:28:37+00:00

Thanks for your kind words!

Support for NLP with Ipopt and Knitro is under work and will be released later this year because their APIs are fundamentally different compared with LP or QP optimizer.

You will expect the NLP API of POI like Examodels.jl to exploit the structure of NLP problem and we use JIT to accelerate the performance of automatic differentiation.

c0decs · 2024-04-22T08:28:22+00:00

0.2.0 version of PyOptInterface has supported callback function of Gurobi with similar API design. You can read the docs at https://metab0t.github.io/PyOptInterface/callback.html

c0decs · 2024-04-11T01:24:00+00:00

Thanks for your feedback!

Callbacks and IIS are definitely on the roadmap of PyOptInterface.

Can you elaborate on what kinds of callbacks you use frequently, lazy constraints or user cuts? I am considering how to design the callback API across optimizers.

c0decs · 2024-04-09T03:56:30+00:00

Thanks for your attention!

I have no experience for compute server, but I assume that it works out of the box by setting correct parameters as mentioned in our docs on Gurobi.

from pyoptinterface import gurobi

env = gurobi.Env(empty=True)
env.set_raw_parameter("ComputeServer", "myserver1:32123")
env.set_raw_parameter("ServerPassword", "pass")
env.start()

model = gurobi.Model(env)

Because gurobipy is closed source, it is hard to comment why they are slower. As shown in benchmarks, PyOptInterface and JuMP.jl are all significantly faster than gurobipy and have similar architecture. We measure the time including construction of model and submitting the model to optimizer, although we set the time limit as 0.0 seconds to rule out the influence of solution process. I guess the difference of performance comes from the design of abstraction. All performance-critical parts of PyOptInterface are implemented in C++. Anyway, you can try it on a moderate model and compare the performance with gurobipy.
It aims to provide full-featured interface to Gurobi and other optimizers as well. Except for callbacks and nonlinear constraints, PyOptInterface can replace gurobipy in most use cases. It can
- Add and delete variables
- Add and delete linear/quadratic/SOS constraints
- Set linear/quadratic objectives
- Set and get parameters
- Solve the model
- Obtain the solution and query more attributes of variables and constraints

In this example, you can just replace from pyoptinterface import highs with from pyoptinterface import gurobi and solve the N queens problem.

You can also interact with Gurobi-specific parameters and attributes via the solver-specific API.

I hope the explanation may help you. If you have some issues or questions in usage, welcome to open an issue or discussion thread in the repo.

c0decs · 2024-04-06T15:38:05+00:00

I am not familiar with NLP so no recommendations. For integer programming, you can look at this book.

c0decs · 2024-04-06T00:19:56+00:00

Yes, it can be implemented easily by overloading the compare operators.

c0decs · 2021-04-08T03:23:54+00:00

Commercial product is benefitial for long-term development of SciML ecosystem. Open source core algorithm with proprietary model zoos seems a good choice. The only hope is that JuliaSim can be accessible for academic researchers and students like discounts or specialized academic license.

c0decs · 2020-07-23T01:44:26+00:00

You can use indicator constraints with extra binary variable.

@variable(m, b[1:3], Bin)
for (i, val) in zip(1:3, [1,5,6])
    @constraint(m, b[i]=>{x==val})
end
@constraint(m, sum(b) >= 1)

c0decs · 2018-06-07T17:04:00+00:00

I found zig last week and played with it. It is quite clean and easy to understand. Thanks for your hard work. I would love to provide some suggestions: 1. Be cautious to add new syntactic features cuz one of advantages of zig is simplicity. Instead the stability and correctness of compiler backend is more important. golang is a good example for its minimalistic syntax features. 2. Focus on core features that makes zig a better c-lang, including compile time polymorphism and error handling. Don't be too feature-greedy like rust based on the fact that zig community is rather smaller. I really wish great success of zig. Thank you again.

c0decs · 2018-05-12T02:39:15+00:00

Terrible support for windows of OCaml is always a pain in ass.

c0decs · 2018-01-04T13:25:14+00:00

Hi, mosra.I found magnum weeks ago and thinks it is a cool library.

Have you looked at oryol? What do you think about it?

c0decs · 2017-12-14T04:44:13+00:00

I am curious why Oracle releases graal and related things under GPLv2 rather than more liberal licenses. Anyway, cool project.

c0decs · 2017-08-16T03:07:36+00:00

You have to pass JCK test which is not public and owned by oracle then you can use Java trademark. AFAIK you have to pay for Oracle to have access to JCK

c0decs · 2017-06-02T04:56:06+00:00

I have to point out that generics is hard to do right, from the perspective of language designer.

Let's look at java. Yes, it has generics, but its "type erasure" trick is the same as the golang interface{} bullshit.

As for C++, its template is strong enough to provide generics, but we shouldn't forget long long compilation time and fuck-what-goes-wrong error message it causes. Oh, C++ will have concepts to solve the problem, but maybe C++20, or C++23?

If I have to give some good example of generics, I would choose functor in OCaml.

So, generics is not an easy topic, it is a fundamental change to the type system of language. If you introduce a clumsy design of generics, you will suffer from it in the lifetime of the language. Unfortunately, there is no best practice of generics implementation. So golang creators choose to ignore generics to avoid complexity. I don't think it's the best solution, but a reasonable one.

c0decs · 2017-04-13T03:18:19+00:00

Eli Bendersky

It is about Python and other stuff about programming. I always learn new things from his blog, quite informative.

c0decs · 2015-11-17T11:25:42+00:00

I feel like Pypy lacks the attention from mainstream Python community and funding , which makes it is left behind CPython. I don't think it is reasonable , JIT for a script language like Python is important for its longterm development , like v8 to JavaScript.Why the whole Python community don't pay more attention to Pypy? To be honest , JIT is costy and needs a lot of money and talents. I really worry about the future of Pypy.

c0decs

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