TypeError of the `csdl_om` simulator object

[RuruX]

Hi Victor,

I was trying to build a CustomImplicitOperation object corresponding to the OpenMDAO ImplicitComponent class. I assume they are using the same methodology except for the syntax differences.

However, I was having trouble to simulate the model using csdl_om, that the error popped up saying "TypeError: CSDL-OM only accepts CSDL Model specifications to construct a Simulator." Here is the complete error message when running the ex_custom.py in the CSDL repository, with simulator defined with it.

Traceback (most recent call last):
  File "csdl_test.py", line 50, in <module>
    sim = Simulator(ExampleImplicitSimple())
  File "/home/ru/csdl_om/csdl_om/core/simulator.py", line 49, in __init__
    raise TypeError(
TypeError: CSDL-OM only accepts CSDL Model specifications to construct a Simulator.

And the complete code example I'm using is as below.

from csdl import CustomExplicitOperation, CustomImplicitOperation, NewtonSolver, ScipyKrylov
import csdl
import numpy as np


class ExampleImplicitSimple(CustomImplicitOperation):
    """
    :param var: x
    """
    def define(self):
        print("="*40)
        print(" Running define()...")
        print("="*40)
        self.add_input('a', val=1.)
        self.add_input('b', val=-4.)
        self.add_input('c', val=3.)
        self.add_output('x', val=0.)
        self.declare_derivatives('x', 'x')
        self.declare_derivatives('x', ['a', 'b', 'c'])

        self.linear_solver = ScipyKrylov()
        self.nonlinear_solver = NewtonSolver(solve_subsystems=False)

    def evaluate_residuals(self, inputs, outputs, residuals):
        print("="*40)
        print(" Running evaluate_residual()...")
        print("="*40)
        x = outputs['x']
        a = inputs['a']
        b = inputs['b']
        c = inputs['c']
        residuals['x'] = a * x**2 + b * x + c

    def compute_derivatives(self, inputs, outputs, derivatives):
        print("="*40)
        print(" Running compute_derivatives()...")
        print("="*40)
        a = inputs['a']
        b = inputs['b']
        x = outputs['x']

        derivatives['x', 'a'] = x**2
        derivatives['x', 'b'] = x
        derivatives['x', 'c'] = 1.0
        derivatives['x', 'x'] = 2 * a * x + b
        
from csdl_om import Simulator

# Generate an implementation.
sim = Simulator(ExampleImplicitSimple())
# Run simulation.
sim.run()
# Access values
print(sim['x'])

It seems that the CustomImplicitOperation object is not recognized by the simulator as a valid input, which should be a model object (here). Or it could also be me using the simulator wrong. Please let me know what you think.

Best,
Ru

Meta

Here are the versions of CSDL and CSDL-OM I was using, which are both the latest as of the issue report.

Backtrace

<backtrace>

[vgucsd]

You will need to call csdl.custom from within a Model subclass and construct a Simulator from that Model. You cannot construct a Simulator from anything other than a Model. Consider the following:

from csdl import Model
from csdl_om import Simulator

class M(Model):
    def define(self):
        a = self.declare_variable('a', val=1.)
        b = self.declare_variable('b', val=-4.)
        c = self.declare_variable('c', val=3.)

        x = csdl.custom(a, b, c, op=ExampleImplicitSimple())
        self.register_output('x', x)

sim = Simulator(M())
sim.run()
print(sim['x'])

This produces the following output:

======================
custom_implict_op_0003
======================
NL: Newton Converged in 5 iterations
[1.]

A few things to note here:

• The values in the calls to declare_variable will overwrite the values in ExampleImplicitSimple.
• For now, the variable arguments passed to csdl.custom must share the same name as the inputs added using add_input. They must also be in the same order as the calls to add_input. For example, if you were to switch a and b such that csdl.custom(b, a, c, op=ExampleImplicitSimple()), you would get different behavior, and an error if a and b are different shapes. In the future, the names will not need to match the names used within ExampleImplicitSimple.
• Because csdl.custom is not a Model method, it cannot register outputs automatically. Just like any other standard library function, the output must be registered. Again, for now, the name must match the name defined in add_output, so self.register_output('y', x) would not produce the right behavior.
• Unlike the object returned by Model.create_implicit_operation when defining implicit relationships with a Model subclass, the ExampleImplicitSimple class needs to set its solver within the define method, unless you instantiate it outside the call to csdl.custom like so:

e = ExampleImplicitSimple()
e.linear_solver = ScipyKrylov()
e.nonlinear_solver = NewtonSolver(solve_subsystems=False)
x = csdl.custom(a, b, c, op=e)

The reason I mention this is that you may want to leave the solvers out of the class definition until the user of your custom operation decides to use it, and you can leave it up to the user to decide what solvers to use.

[vgucsd]

I added the documentation label because this is something I have planned to document, but haven't yet gotten around to doing so.

[RuruX]

Thank you so much for your explanation! It has exactly solved my problem. And looking forward to seeing this represented in the documentation.

[vgucsd]

Since I've labeled this a documentation issue and this hasn't been documented, I'm reopening it.