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logdet value becomes nan, when I used the UCR dataset named FaceDetecion.
I chosed the BERT model to deal with the multiple timeseries data.
I wonder why this happened?
The text was updated successfully, but these errors were encountered:
def forward(self, X, Y, num_classes=None):
if num_classes is None:
num_classes = Y.max() + 1
X = F.normalize(X, dim=-1)
W = X.T
Pi = tf.label_to_membership(Y.numpy(), num_classes)
Pi = torch.tensor(Pi, dtype=torch.float32).cuda()
logdet value becomes nan, when I used the UCR dataset named FaceDetecion.
I chosed the BERT model to deal with the multiple timeseries data.
I wonder why this happened?
The text was updated successfully, but these errors were encountered: