I have a few doubts regarding padding sequences in a LSTM/GRU:-


If the input data is padded with zeros and suppose 0 is a valid index in my Vocabulary, does it hamper the training


After doing a pack_padded_sequence , does Pytorch take care of ensuring that the padded sequences are ignored during a backprop


Is it fine to compute loss on the entire padded sequence


While evaluating, I use value of the final hidden state h_n as the one for my prediction tasks. Is this value already corrupted by my input sequence padding?