Hi,
in “Returning sequences” section of the lesson 6 notebook Why the zeros vector has this shape
In [68]:
zeros = np.tile(np.zeros(n_fac), (len(xs[0]),1))
zeros.shape
Out[68]:
(75110, 42)
This is equal to (number of samples X n_fac). why?
And a question about Embedding.
Each layer of Embedding is different from the others. because in the summary Keras counts 3570 (85*42) parameters for each embedding layer. That means each character in the sequence gains different n_fac = 42
parameters in different layers. Am I understanding correct?
Does the output of the Embedding have the size of n_fac = 42
?
thanks