Reputation: 23
I want to use time as an input feature to my deep learning model. So I need to use Embedding layer to convert it to embedded vectors. SO I used:
from keras.layers import Embedding
hours_input=Input(shape=(1,),name='hours_input')
hours_embedding=Embedding(24,64)hours_input
I need the output of Embedding layer (weights I mean). I used hours_embedding.get_weights(). But I got an error: get_weights() missing 1 required positional argument: 'self' So, How can I get embedding weight matrix?
Upvotes: 1
Views: 967
Reputation: 3564
Create your model First.
hours_input=Input(shape=(1,),name='hours_input')
hours_embedding=Embedding(24,64)(hours_input)
model = keras.models.Model(inputs = hours_input, outputs = hours_embedding)
And then you can access:
model.layers[1].get_weights()
Output:
[array([[ 0.00782292, -0.03037642, -0.03229956, ..., -0.02188529,
-0.02597365, -0.04166167],
[-0.04877049, -0.03961046, 0.01000347, ..., 0.00204592,
0.01949279, -0.00540505],
[ 0.0323245 , -0.02847096, -0.0023482 , ..., 0.02859743,
-0.04320076, 0.01578701],
...,
[ 0.01989252, 0.00970422, 0.00193944, ..., 0.02689132,
-0.00167314, 0.00353283],
[ 0.01885528, 0.00589638, -0.03409225, ..., -0.00504225,
0.01269731, 0.04380948],
[-0.01756806, -0.00950485, -0.0189078 , ..., 0.023773 ,
-0.00471363, -0.03708603]], dtype=float32)]
Upvotes: 2