Hi all,
Let’s say I have a class called NonLinearProblem
which solves a specific type of problem, give different values to its arguments. After instantiating a object from this class, one only needs to pass a numpy array to this object like to do the computation. I have also access to analytically obtained gradients
nlp = NonLinearProblem(constraints, #other_args)
input = np.randn(5, ) # any 1D array
# forward function
nlp.__objective(input) # returns is a scalar
# backward function
nlp.__gradient(input) # returns array with the same shape of input
Now, I want to extend autograd.Function
to use this class and its corresponding .__objective
and .__gradient
in forward
and backward
respectively.
This is what I have done so far:
# I init `nlp` outside of Function
class TopoptFunction2(autograd.Function):
@staticmethod
def forward(ctx, densities: torch.Tensor, nlp):
# tps.setOverallDensities()
output = nlp.__objective(densities.data.numpy())
ctx.save_for_backward(densities, nlp)
return torch.FloatTensor(output)
@staticmethod
def backward(ctx, grad_output):
densities, nlp = ctx.saved_tensors
# tps.setOverallDensities(densities.data.numpy())
objective_gradient = nlp.__gradient(densities.data.numpy())
return torch.FloatTensor(objective_gradient * grad_output), None
I am trying to gradcheck
by:
topopt = TopoptFunction2.apply
dummy_in = torch.empty(100, dtype=torch.float64).fill_(0.6)
dummy_in.requires_grad = True
test = autograd.gradcheck(topopt, (dummy_in, nonLinearProblem), eps=1e6, atol=1e4)
print(test)
But in forwad
, I get a strange error where an attirbute combined with name of class and method is trying to be called which obviously does not exist:
Traceback (most recent call last):
File "/home/nikan3/diffvoxelfemoptimizationproblem/VoxelFEM/python/demo_1.py", line 219, in <module>
test = autograd.gradcheck(topopt, (dummy_in, nonLinearProblem), eps=1e6, atol=1e4)
File "/home/nikan3/.local/lib/python3.6/sitepackages/torch/autograd/gradcheck.py", line 323, in gradcheck
func_out = func(*tupled_inputs)
File "/home/nikan3/diffvoxelfemoptimizationproblem/VoxelFEM/python/demo_1.py", line 187, in forward
output = nlp.__objective(densities.data.numpy())
AttributeError: 'cyipopt.problem' object has no attribute '_TopoptFunction2__objective'
As you can see, somehow _[ClassName][attributeName]
is being called!
Some further details:

cyipopt.problem
istype(nlp)
 I have created python bindings for this package and it works fine except in this issue
Thanks for your suggestions and comments
Bests