How to duplicate parameters?

Hi all,

I’m new to pytorch, so this may be a trivial question, but still. I’m trying to create one set of parameters, and “duplicate” it multiple times, like this:

self.vb = nn.Parameter(torch.FloatTensor(64))
self.var_bias =[self.vb]*10)

I’m then only using self.var_bias throughout my model. I was thinking of it as a fixed computation graph, meaning self.var_bias is the concatenation of 10 identical copies of self.vb . I expected (self.var_bias[:64] == self.vb) to be always True. However, if I put a breakpoint after a couple of hundred of iterations, I see thats not the case. What am I missing here? did create a new Variable entirely detached from self.vb ?


self.var_bias =[self.vb]*10) is executed in the constructor right? returns a new Variable that does not share storage with the previous variable.

If self.var_bias is changed, self.vb does not automatically change unless you re-execute the line self.var_bias =[self.vb]*10). (the Variable history is saved, but the memory locations are not shared).

What you are looking for is probably expand, which inflates the size in a particular dimension, but also shares the underlying storage.

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