student t-distribution, as same as used in t-SNE algorithm. q_ij = 1/(1+dist(x_i, u_j)^2), then normalize it. Arguments: inputs: the variable containing data, shape=(n_samples, n_features) Return: q: student's t-distribution, or soft lab
(self, inputs, **kwargs)
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