title: How to get the values of weights and biases of keras layer?
body: <p>To make my question more clear, here I wrote a piece of code:</p>
  
  <pre><code>from keras.layers import Input, Dense
  from keras.models import Model
  import numpy as np
  
  features = np.random.normal(0, 1, (1000, 3))
  labels = np.sum(features, axis=1)
  print(features.shape, labels.shape)
  
  input_layer = Input(shape=(3,))
  dense_layer_1 = Dense(units=10, activation='sigmoid')
  dense_layer_1_output = dense_layer_1(input_layer)
  dense_layer_2 = Dense(units=1, activation='linear')
  dense_layer_2_output = dense_layer_2(dense_layer_1_output)
  
  model = Model(input_layer, dense_layer_2_output)
  model.compile(optimizer='adam', loss='mean_squared_error')
  model.fit(features, labels, batch_size=32, epochs=20, verbose=2, validation_split=.2)
  </code></pre>
  
  <p>My question is: how to fetch and print the value of weights and biases of these two Dense layers?</p>