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Visual Code Python debugging tool crashes when trying to access "Model" object attributes before optimization
Consider the following code to model the maximum independent set problem to solve the maximum clique using MIP and NetworkX:
import mip
import networkx
n = 2 ** 3
g = networkx.binomial_tree(n)
networkx.add_star(g, [i for i in range(n)])
g1 = networkx.complement(g)
model = mip.Model("Independent Set")
x = [model.add_var(var_type=mip.BINARY) for _ in range(len(g1.nodes))]
model.objective = mip.maximize(mip.xsum(x[i] for i in range(len(g1.nodes))))
for (i, j) in g1.edges:
model += x[i] + x[j] <= 1
model.optimize()
selected = [i for i in range(len(g1.nodes)) if x[i].x >= 0.99]
print(selected)
g2 = g.subgraph(selected)
If I try to access the model variables in the watch section, it gives he following message on terminal:
Information not available, model was not optimized yet.
And then, the debugger dies. I believe this is not what should happen, some help with this?
Hello Otávio !
Currently we throw an exception when an specific property of a variable (the solution value x) is accessed, since the debugger is probably trying to access all properties we have this problem...
I think that the behaviour could be changed to just return None as solution value when no optimization is performed. I'll include this change in the next release.
Cheers,
Haroldo
--
Haroldo Gambini Santos Computing Department Universidade Federal de Ouro Preto - UFOP email: [email protected] [email protected] home/research page: www.decom.ufop.br/haroldo
It has long been an axiom of mine that the little things are infinitely the most important. -- Sir Arthur Conan Doyle, "A Case of Identity"
On Wed, 20 Nov 2019, Otávio Augusto Silva wrote:
Consider the following code to model the maximum independent set problem to solve the maximum clique using MIP and NetworkX:
import mip import networkx
n = 2 ** 3 g = networkx.binomial_tree(n) networkx.add_star(g, [i for i in range(n)]) g1 = networkx.complement(g)
model = mip.Model("Independent Set") x = [model.add_var(var_type=mip.BINARY) for _ in range(len(g1.nodes))] model.objective = mip.maximize(mip.xsum(x[i] for i in range(len(g1.nodes)))) for (i, j) in g1.edges: model += x[i] + x[j] <= 1 model.optimize() selected = [i for i in range(len(g1.nodes)) if x[i].x >= 0.99] print(selected) g2 = g.subgraph(selected)
If I try to access the model variables in the watch section, it gives he following message on terminal:
Information not available, model was not optimized yet.
And then, the debugger dies. I believe this is not what should happen, some help with this?
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Strange, which attribute triggered the exception ?
Em dom, 1 de dez de 2019 12:19, Otávio Augusto Silva < [email protected]> escreveu:
I updated MIP and checked yesterday and the same behaviour continues
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I'm not sure, Visual Code shows my all attributes of the object, but I can't see any because the debugger dies before anything shows up. Not sure if relevant, but the same thing happens on Jupyter notebooks, if I use the tab key to show the attributes of the object, the kernel also dies.
The object that you tried to inspect in the debugger is a variable ? Right now (1.6) no exception is thrown while querying variable contents, so I don't know where to look
It is, in my example code it's the model variable, before running the model.optimize() line.
Hi @otavio-silva , could you provide your code (or better, an small example) where it happens so that I can check if this is solved ?
@h-g-s here's an example modelling the 0-1 Knapsack problem:
import mip
p = [825594, 1677009, 1676628, 1523970, 943972, 97426, 69666, 1296457, 1679693, 1902996, 1844992, 1049289, 1252836, 1319836, 953277, 2067538, 675367, 853655, 1826027, 65731, 901489, 577243, 466257, 369261]
w = [382745, 799601, 909247, 729069, 467902, 44328, 34610, 698150, 823460, 903959, 853665, 551830, 610856, 670702, 488960, 951111, 323046, 446298, 931161, 31385, 496951, 264724, 224916, 169684]
c = 6404180
n = len(w)
model = mip.Model("Knapsack")
x = [model.add_var(var_type=mip.BINARY) for _ in range(n)]
model.objective = mip.maximize(mip.xsum(p[i] * x[i] for i in range(n)))
model += mip.xsum(w[i] * x[i] for i in range(n)) <= c
model.optimize()
selected = [i for i in range(n) if x[i].x >= 0.99]
print(selected)
If I try to inspect the model variable before calling model.optimize(), the debugger dies. I'm using Visual Studio code.
Hi @otavio-silva, I am trying to reproduce the error, however everything works fine for me. Can you provide me your python and Visual Studio Code versions?
Sorry for the delay, here's the info:
Python-MIP package version 1.6.4
Python 3.7.5 (default, Oct 31 2019, 15:18:51) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Visual Studio Code 1.41.0
9579eda04fdb3a9bba2750f15193e5fafe16b959
x64
Hi @otavio-silva , just released 1.6.5. There was a case when dual information was being queried when it was not available that was fixed. Maybe this is the cause of your crash. Could you test it ?
hi @otavio-silva , just released 1.6.6 with a fix that may be related to this problem: querying the objective function without optimizing was crashing. Now it returns None if no solution is available. Could you please check again ?
I just tested it with the new version, there's still something causing crashes.