How to get output of hidden layer given an input, weights and biases of the hidden layer in keras?

Question

Suppose I have trained the model below for an epoch:

model = Sequential([
    Dense(32, input_dim=784), # first number is output_dim
    Activation(\'relu\'),
          


        

Answer 1

As for weights, I had a none-Sequential model. What I did was using model.summary() to get the desired layers name and then model.get_layer("layer_name").get_weights() to get the weights.