What is the dense layer for in week 3 assignment?

[arvyzukai]

Hi, @Robert_Garner

I recently answered a similar question explaining the shapes of Tensors that pass through the model:

Understanding the loss of this many to many architecture with LSTM layer

I​ believe I have a problem understanding the basic structure of this architecture used in week 3 graded assignment that tackles NER. W​hen one input (array of shape (1, max_batch_length, embedding_dimensions)) is fed into the network, does every vector (corresponding to a word in the input) produce an output all the way through the dense layer and the logsoftmax layer? I​f so, shouldn’t the labels also be of the shape (batch_size, max_batch_length, tag_map) ? How is every output that is a …

To answer your question directly:
Dense layer projects LSTM output to as many outputs as you need - 17 in this case - 17 probabilities of one category (tag) or the other.