confused on layer.get_weights()

[周迎威]

Hi, I just monitored the weight update for a simple mlp model:

model=mlp() # contains one input layer in the format of dense, one hidden layer and one output layer.
weight_origin=model.layers[0].get_weights()[0]
model.fit(.....) # with adam optimizer
weight_updated=model.layers[0].get_weights()[0]
print weight_origin-weight_updated

For the first dense layer, I got a matrix of zeros. I thought the training doesn't change this weight. However, weights in other layers are changed. So I'm confused, why the first layer is unchanged? 

I checked the source code but still got no answer, then I tried monitoring:

model.layers[0].get_weights()[1] #get_weight() returns a list of weights

This time, the weights did changed. So I'm wondering which weight is the "true" weight that does working during training? Why there are two elements in the weight list??