I was trying to implement a physics problem where constraints are in the form of 3D arrays. Following code snippet explains the problem setup (only a single constraint was used for the sake of depicting this issue).

```
# grid generation
cs_ar = np.reshape(np.array([[[c_s_0 for i in range(Np_an)] for j in range(N_an)]for k in range(1)]), (1,N_an,Np_an,1))
yp_ar = np.reshape(np.array([[[i*dy_a for i in range(Np_an)] for j in range(N_an)]for k in range(1)]), (1,N_an,Np_an,1))
xp_ar = np.reshape(np.array([[[j*dx_a for i in range(Np_an)] for j in range(N_an)]for k in range(1)]), (1,N_an,Np_an,1))
tp_ar0 = np.reshape(np.array([[[0.0 for i in range(Np_an)] for j in range(N_an)]for k in range(1)]), (1,N_an,Np_an,1))
#Constraint
IC_an = PointwiseConstraint.from_numpy(
nodes=nodes,
invar={"x":xp_ar, "y":yp_ar, "t":tp_ar0},
outvar={"c_s":cs_ar},
batch_size=4,
)
domain.add_constraint(IC_an, "IC_an")
```

But the execution is stalling before the training starts

```
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - Arch Node: battery_network has been converted to a FuncArch node.
[05:49:23] - attempting to restore from: outputs/Diffusion_numpy
[05:49:23] - optimizer checkpoint not found
[05:49:23] - model battery_network.0.pth not found
```

The execution does not proceed after this point. I waited for more than an hour.

This issue is not present when 1D arrays as expressed below are used for specifying constraints

```
cs_ar = np.reshape(np.array([c_s_0 for i in range(N_an*Np_an*1)]), (N_an*Np_an*1,1))
yp_ar = np.reshape(np.array([c_s_0 for i in range(N_an*Np_an*1)]), (N_an*Np_an*1,1))
xp_ar = np.reshape(np.array([c_s_0 for i in range(N_an*Np_an*1)]), (N_an*Np_an*1,1))
tp_ar0 = np.reshape(np.array([0.0 for i in range(N_an*Np_an*1)]), (N_an*Np_an*1,1))
```

I tried to implement the same constraint with 2D arrays of the form

```
cs_ar = np.reshape(np.array([[c_s_0 for i in range(Np_an)] for j in range(N_an)]), (N_an,Np_an,1))
yp_ar = np.reshape(np.array([[c_s_0 for i in range(Np_an)] for j in range(N_an)]), (N_an,Np_an,1))
xp_ar = np.reshape(np.array([[c_s_0 for i in range(Np_an)] for j in range(N_an)]), (N_an,Np_an,1))
tp_ar0 = np.reshape(np.array([[c_s_0 for i in range(Np_an)] for j in range(N_an)]), (N_an,Np_an,1))
```

and got the following error.

```
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:16] - Arch Node: battery_network has been converted to a FuncArch node.
[04:19:17] - attempting to restore from: outputs/Diffusion_numpy
[04:19:17] - optimizer checkpoint not found
[04:19:17] - model battery_network.0.pth not found
Error executing job with overrides: []
An error occurred during Hydra's exception formatting:
AssertionError()
Traceback (most recent call last):
File "/opt/conda/lib/python3.8/site-packages/hydra/_internal/utils.py", line 252, in run_and_report
assert mdl is not None
AssertionError
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "Battery_numpy.py", line 278, in <module>
run()
File "/modulus/modulus/hydra/utils.py", line 91, in func_decorated
_run_hydra(
File "/opt/conda/lib/python3.8/site-packages/hydra/_internal/utils.py", line 377, in _run_hydra
run_and_report(
File "/opt/conda/lib/python3.8/site-packages/hydra/_internal/utils.py", line 294, in run_and_report
raise ex
File "/opt/conda/lib/python3.8/site-packages/hydra/_internal/utils.py", line 211, in run_and_report
return func()
File "/opt/conda/lib/python3.8/site-packages/hydra/_internal/utils.py", line 378, in <lambda>
lambda: hydra.run(
File "/opt/conda/lib/python3.8/site-packages/hydra/_internal/hydra.py", line 111, in run
_ = ret.return_value
File "/opt/conda/lib/python3.8/site-packages/hydra/core/utils.py", line 233, in return_value
raise self._return_value
File "/opt/conda/lib/python3.8/site-packages/hydra/core/utils.py", line 160, in run_job
ret.return_value = task_function(task_cfg)
File "Battery_numpy.py", line 272, in run
slv.solve()
File "/modulus/modulus/solver/solver.py", line 159, in solve
self._train_loop(sigterm_handler)
File "/modulus/modulus/trainer.py", line 593, in _train_loop
self._record_constraints()
File "/modulus/modulus/trainer.py", line 275, in _record_constraints
self.record_constraints()
File "/modulus/modulus/solver/solver.py", line 116, in record_constraints
self.domain.rec_constraints(self.network_dir)
File "/modulus/modulus/domain/domain.py", line 45, in rec_constraints
constraint.save_batch(constraint_data_dir + key)
File "/modulus/modulus/domain/constraint/continuous.py", line 77, in save_batch
var_to_polyvtk(save_var, filename)
File "/modulus/modulus/utils/io/vtk.py", line 945, in var_to_polyvtk
points = np.concatenate(points, axis=1)
File "<__array_function__ internals>", line 180, in concatenate
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 3 dimension(s) and the array at index 2 has 2 dimension(s)
```

Is it because multidimensional arrays are not supported in modulus constraints?