MultiObjectiveOptimization
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local variable 'sol' referenced before assignment
I encounter an error UnboundLocalError: local variable 'sol' referenced before assignment
In min_norm_solvers.py,
def _min_norm_2d(vecs, dps):
"""
Find the minimum norm solution as combination of two points
This is correct only in 2D
ie. min_c |\sum c_i x_i|_2^2 st. \sum c_i = 1 , 1 >= c_1 >= 0 for all i, c_i + c_j = 1.0 for some i, j
"""
dmin = 1e8
for i in range(len(vecs)):
for j in range(i+1,len(vecs)):
if (i,j) not in dps:
dps[(i, j)] = 0.0
for k in range(len(vecs[i])):
dps[(i,j)] += torch.mul(vecs[i][k], vecs[j][k]).sum().data.cpu()
dps[(j, i)] = dps[(i, j)]
if (i,i) not in dps:
dps[(i, i)] = 0.0
for k in range(len(vecs[i])):
dps[(i,i)] += torch.mul(vecs[i][k], vecs[i][k]).sum().data.cpu()
if (j,j) not in dps:
dps[(j, j)] = 0.0
for k in range(len(vecs[i])):
dps[(j, j)] += torch.mul(vecs[j][k], vecs[j][k]).sum().data.cpu()
c,d = MinNormSolver._min_norm_element_from2(dps[(i,i)], dps[(i,j)], dps[(j,j)])
if d < dmin:
dmin = d
sol = [(i,j),c,d]
return sol, dps
The sol variable is only assigned if d < dmin, what if d >= dmin always, what should the sol variable be? I assume that it will be sol = [(i,j),c,dmin], is that right?
