LSTM and encoder_layers

Well, to be more precise:

technically speaking embeddings are after the embedding layer, and these should be called representations… (but I’m not a big fan of terminology because different people use different or same words to communicate), so your picture should look more like:

“It’s” ----tokenized-----> [54] ----embedded----> [0.1, 0.3, 0.5, 07] (and this vector would be called embeddings).

Now the first LSTM (and the second) are missing arrows from left sides (each rectangle receives previous “hidden states”), for the first state for example that would be [0, 0, 0, 0]

The top rectangles would be the representations of each word. (I cannot draw you a scheme right now but your second picture in the previous post pretty much is a good representation of what happens (we don’t use the softmax in the encoder)).

You might find this thread (with actual number values) helpful.