STAM
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How to train?
Hi, Thanks for this implementation. But I still have some problems. The parameters in model are initialize as follow:
def _init_weights(self, m):
if isinstance(m, nn.Linear):
with torch.no_grad():
trunc_normal_(m.weight, std=.02)
if isinstance(m, nn.Linear) and m.bias is not None:
nn.init.constant_(m.bias, 0)
elif isinstance(m, nn.LayerNorm):
nn.init.constant_(m.bias, 0)
nn.init.constant_(m.weight, 1.0)
Does this mean I should make these parameters trainable when I train this model on my own dataset?