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POT sinkhorn_stabilized and sinkhorn_epsilon_scaling methods for sinkhorn getting stuck #748
I am running sinkhorn between two datasets of 100 images (each 28x28 -- this is just 2 subsets of fashionmnist), but for some reason, I am finding that the sinkhorn_epsilon_scaling method is getting stuck at a certain value (I have attached the log), no matter if regularization is 0.0001, 0.001, 0.01, 0.1, 1. It is the same for different datasets of the same size -- why is this?
N = len(data1['ys'])
X = torch.stack(data1[feature]).reshape((N, -1)).to(torch.float64)
Y = torch.stack(data2[feature]).reshape((N, -1)).to(torch.float64)
M = ot.dist(X, Y)
Mmax = M.max()
M_normalized = M / Mmax if float(Mmax) != 0.0 else M
a = torch.full((N,), 1.0 / N, dtype=torch.float64)
b = torch.full((N,), 1.0 / N, dtype=torch.float64)
W, log = ot.sinkhorn(
a, b, M_normalized,
reg=reg,
method=method,
numItermax=numItermax,
verbose=is_verbose,
log=True,
warn = True
)
Activity
annabel-ma commentedon Aug 13, 2025
I am using torch float64 tensors
annabel-ma commentedon Aug 13, 2025