Hi, I am using modulus 22.09 to train a model that provide flow field prediction for a 2D airfoil with changing angle of attack and inlet velocity.

However, I encountered a unroll graph error on the pointwisemonitor part, here is the error log:

```
[19:05:28] - JitManager: {'_enabled': False, '_arch_mode': <JitArchMode.ONLY_ACTIVATION: 1>, '_use_nvfuser': True, '_autograd_nodes': False}
[19:05:28] - GraphManager: {'_func_arch': True, '_debug': False, '_func_arch_allow_partial_hessian': True}
[19:08:11] - Arch Node: flow_network has been converted to a FuncArch node.
[19:13:42] - Arch Node: flow_network has been converted to a FuncArch node.
integral continuity NOT implemented.
[19:14:09] - Arch Node: flow_network has been converted to a FuncArch node.
####################################
could not unroll graph!
This is probably because you are asking to compute a value that is not an output of any node
####################################
invar: [x, y, sdf, area, aoa, x_pos]
requested var: [continuity, momentum_x, momentum_y]
computable var: [x, y, sdf, area, aoa, x_pos, continuity]
####################################
Nodes in graph:
node: Sympy Node: continuity
evaluate: SympyToTorch
inputs: []
derivatives: [u__x, v__y]
outputs: [continuity]
optimize: False
node: Sympy Node: momentum_x
evaluate: SympyToTorch
inputs: [u, v]
derivatives: [p__x, u__x, u__x__x, u__y, u__y__y]
outputs: [momentum_x]
optimize: False
node: Sympy Node: momentum_y
evaluate: SympyToTorch
inputs: [u, v]
derivatives: [p__y, v__x, v__x__x, v__y, v__y__y]
outputs: [momentum_y]
optimize: False
node: Sympy Node: normal_dot_vel
evaluate: SympyToTorch
inputs: [normal_x, normal_y, u, v]
derivatives: []
outputs: [normal_dot_vel]
optimize: False
node: Arch Node: flow_network
evaluate: FullyConnectedArch
inputs: [x, y, aoa, vel_in]
derivatives: []
outputs: [u, v, p]
optimize: True
####################################
```

Here is how I set the flow nodes:

```
# parametric variation
vel_in = Symbol("vel_in")
vel_in_range = (0.0,10.0)
vel_param = {vel_in:vel_in_range}
inlet_vel = (vel_in,0.0)
nonslip_vel = (0.0,0.0)
outlet_p = 0.0
volumetric_flow = 20.0*vel_in # this one for integral continuity
# physical quantities
kinematic_viscosity = 0.01
ref_length = 1.
Re = inlet_vel[0]*ref_length/kinematic_viscosity
inv_Re = 1./Re
rho = 1.0
# make navier stokes equations
if cfg.custom.turbulent:
ze = ZeroEquation(nu=0.002, dim=2, time=False, max_distance=0.5)
ns = NavierStokes(nu=ze.equations["nu"], rho=1.0, dim=2, time=False)
navier_stokes_nodes = ns.make_nodes() + ze.make_nodes()
else:
ns = NavierStokes(nu=0.01, rho=1.0, dim=2, time=False)
navier_stokes_nodes = ns.make_nodes()
normal_dot_vel = NormalDotVec(["u", "v"])
# make network arch
if cfg.custom.parameterized:
input_keys = [
Key("x"),
Key("y"),
Key("aoa"),
Key("vel_in"),
]
else:
input_keys = [Key("x"), Key("y")]
flow_net = FullyConnectedArch(
input_keys=input_keys, output_keys=[Key("u"), Key("v"), Key("p")]
)
# make list of nodes to unroll graph on
flow_nodes = (
navier_stokes_nodes
+ normal_dot_vel.make_nodes()
+ [flow_net.make_node(name="flow_network")]
)
```

Here is the PointwiseMonitor that have the unroll graph error:

```
# add monitors
global_monitor = PointwiseMonitor(
geo.volume_geo.sample_interior(1000),
#invar = ["vel_in"],
output_names=["continuity", "momentum_x", "momentum_y"],
metrics={
"mass_imbalance": lambda var: torch.sum(
var["area"] * torch.abs(var["continuity"])
),
"momentum_imbalance": lambda var: torch.sum(
var["area"]
* (torch.abs(var["momentum_x"]) + torch.abs(var["momentum_y"]))
),
},
nodes=flow_nodes,
requires_grad=True,
)
domain.add_monitor(global_monitor)
```

Can somebody kindly help me with this unroll graph error?

Best regards.