So, the input is my embedding layer right? And embedding is simply a lookup created for each word in a sentence.
Let’s say my vocab size = 10 and I define my embedding dim = 5. So, each word in my vocab is represented as a 1x5 vector. Now, this vector in input into the RNN.
What I cannot seem to wrap my around is that if I have two sentence of lengths 6 words and 8 words, then I will send vectors of length 6 and 8 to the RNN each of which is a 1x5 vector. But I still have to decide on the input length right?
In PyTorch RNN, seq_len is the length of our input that we want to consider, right? In this case, if seq_len is not deciding the number of neurons, then what is?