CODEWITHSUNDEEP
pythonpyomo
Jasper
Jasper

Reputation: 103

How to save (pickle) a model instance in pyomo

I want to create a model instance and then save it so I can load and solve at a later time (the initialization takes quite long compared to the solving). When I tried this it gave me the following error.

with open('model.pickle', 'w') as f:
    pickle.dump(instance, f)

AttributeError: Can't pickle local object 'Euphemia.init..obj_expression

The objective function is this:

    def obj_expression(model):
        curve = sum(model.x[area, hour, Type, index] * model.Q[area, hour, Type, index] * 
                    ( model.P1[area, hour, Type, index] + model.P0[area, hour, Type, index] ) / 2  
                        for (area, hour, Type, index) in model.Curve )
        bids = sum(model.y[area, index] * model.PB[area, index] * 
                       sum( model.QB[area, index, hour] for (hour) in model.Hours ) 
                               for (area, index) in model.Bids  )
        return curve + bids
    self.model.OBJ = pe.Objective(rule = obj_expression, sense = pe.maximize)

does anybody know how to save a concrete model?

Upvotes: 2

Views: 4120

Answers (2)

Rob
Rob

Reputation: 13

It looks like pickle (and also cloudpickle) will not work when DerivativeVar is used.

from pyomo.environ import *
from pyomo.dae import *
import pickle
import dill
model = ConcreteModel()
model.x = ContinuousSet(initialize=(0., 1.))
model.y = Var(model.x, initialize=1.)
with open('model1.pickle', 'wb') as f:
    pickle.dump(model, f)

model.dydx = DerivativeVar(model.y, wrt=model.x)
with open('model2.pickle', 'wb') as f:
    try:
        pickle.dump(model, f)
    except TypeError:
        dill.dump(model, f)

dill appears to work instead for pickling a weakref: Pickling weakref in Python

Upvotes: 0

Jasper
Jasper

Reputation: 103

The solution is the cloudpickle module, regular pickle has problems pickling functions. An example:

import cloudpickle

with open('test.pkl', mode='wb') as file:
   cloudpickle.dump(instance, file)


with open('test.pkl', mode='rb') as file:
   instance = cloudpickle.load(file)

Upvotes: 5

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