Why do we need to initialize the hidden state h0 in LSTM in pytorch. As h0 will anyways be calculated and get overwritten ? Isn't it like
int a a = 0
a = 4
Even if we do not do a=0, it should be fine..
The point is that you are able to supply the initial state, it is a feature. They could have implemented it as a default but by letting you control the allocation of the tensor you can save some memory (allocating once, zeroing on every invocation).
Why would you need to set h? Sequence-to-sequence models require this (compress input to one vector, use this vector as hidden state for the decoder) or you might want to make the initial state learnable.
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