As we discussed previously there are various ways you can use the auto-generated optimizer. You can use the generated Rust code, access it over a TCP socket, and so on. In this section we will focus on how to access it directly.

The idea is that OpEn can generate a Python module that you can import.

Generate a Python module for your optimizer​

Consider the following parametric optimization problem:

\[ \begin{align} \operatorname*{Minimize}_{\|u\|\leq r}& \sum_{i=1}^{n_u - 1} b (u_{i+1} - u_{i}^2)^2 + (a-u_i)^2 \\ \text{subject to: }& 1.5 u_1 - u_2 = 0 \\ &u_3 - u_4 + 0.1 \leq 0 \end{align} \]

import opengen as og
import casadi.casadi as cs

u = cs.SX.sym("u", 5)
p = cs.SX.sym("p", 2)
phi = og.functions.rosenbrock(u, p)
c = cs.vertcat(1.5 * u[0] - u[1],
               cs.fmax(0.0, u[2] - u[3] + 0.1))
bounds = og.constraints.Ball2(radius=1.5)
problem = og.builder.Problem(u, p, phi) \
    .with_penalty_constraints(c) \
    .with_constraints(bounds)
build_config = og.config.BuildConfiguration() \
    .with_build_directory("my_optimizers") \
    .with_build_mode("debug") \
    .with_build_python_bindings()
meta = og.config.OptimizerMeta() \
    .with_optimizer_name("rosenbrock")
builder = og.builder.OpEnOptimizerBuilder(problem, meta,
                                          build_config)
builder.build()

Note that we have used with_build_python_bindings().

This will allow us to import the auto-generated optimizer as a Python module!

Use the generated module​

The above code generates an optimizer which is stored in my_optimizers/rosenbrock. In that directory you can find a file called rosenbrock.so (or rosenbrock.pyd on Windows). This can be loaded as an autogenerated Python module. However, mind that this directory is most likely not in your Python path, so you will have to add it before you can import the optimizer. This can be done very easily:

import sys

sys.path.insert(1, './my_optimizers/rosenbrock')
import rosenbrock

Then you will be able to use it as follows:

solver = rosenbrock.solver()
response = solver.run(p=[20., 1.])
if not response.is_ok():
    raise RuntimeError(response.get().message)

result = response.get()
u_star = result.solution

In the first line, solver = rosenbrock.solver(), we obtain an instance of Solver, which can be used to solve parametric optimization problems. In the second line, response = solver.run(p=[20., 1.]), we call the solver with parameter $p=(20, 1)$. Method run accepts another three optional arguments, namely:

• initial_guess (can be either a list or a numpy array),
• initial_lagrange_multipliers, and
• initial_penalty

The solver returns an object of type SolverResponse, similar to the TCP interface. First call response.is_ok() to determine whether the call succeeded, then call response.get() to obtain either a SolverStatus object or a SolverError. This mirrors the Python TCP interface, but without the socket transport layer.

response = solver.run(p=[20., 1.])
if response.is_ok():
    result = response.get()
    u_star = result.solution
else:
    error = response.get()
    print(error.code, error.message)

The returned objects also implement __repr__, which makes them convenient to inspect in a Python REPL or notebook:

response = solver.run(p=[20., 1.])
print(response)
print(response.get())

The SolverStatus object exposes the following properties:

These are the same properties as those of opengen.tcp.SolverStatus.

For backward compatibility, the generated module also exposes OptimizerSolution as an alias of SolverStatus.

If the call fails, response.get() returns a SolverError with:

The most common error codes are:

Importing optimizer with variable name​

Previously we used import rosenbrock to import the auto-generated module.

The limitation of this syntax is that it makes it difficult to change the name of the optimizer, i.e., rosenbrock is hard-coded.

A better syntax would be:

import os
import sys

optimizers_dir = "my_optimizers"
optimizer_name = "rosenbrock"
sys.path.insert(1, os.path.join(optimizers_dir, optimizer_name))
rosenbrock = __import__(optimizer_name)