# Input layer
weights0 = model.layers[0].get_weights()[0]
biases0 = model.layers[0].get_weights()[1]
print("Input layer weights",weights0.shape,":\n",weights0)
print("Input layer biases",biases0.shape,":\n",biases0)

# Hidden layer
weights1 = model.layers[1].get_weights()[0]
biases1 = model.layers[1].get_weights()[1]
print("\nHidden layer weights",weights1.shape,":\n",weights1)
print("Hidden layer biases",biases1.shape,":\n",biases1)

# Output layer
weights2 = model.layers[2].get_weights()[0]
biases2 = model.layers[2].get_weights()[1]
print("\nOutput layer weights",weights2.shape,":\n",weights2)
print("Output layer biases",biases2.shape,":\n",biases2)

Input layer weights (2, 4) :
 [[-0.7894075  3.6576402 -0.5250344  0.9434325]
 [ 0.5507967  1.4482272  0.3676488 -0.662868 ]]
Input layer biases (4,) :
 [ 0.6748611  -2.0139554  -0.08527914  0.8349776 ]

Hidden layer weights (4, 6) :
 [[-1.8434598   1.6634365   1.0989978  -1.2378392   1.7566904   3.6123095 ]
 [-2.7392204   1.6919578  -0.8286774  -1.6898117   0.9557115   4.3050194 ]
 [-1.6529896   1.6501662   2.7722862  -1.7816304   0.41011515  3.199446  ]
 [ 1.8056525   0.28458908 -4.2920456   1.6929411  -0.09055442 -0.7973508 ]]
Hidden layer biases (6,) :
 [ 0.8181632   0.40098986 -0.1719683   0.81605273  0.5744857   0.99497193]

Output layer weights (6, 1) :
 [[ 2.5703835]
 [-1.0549701]
 [-2.5804038]
 [ 1.6665599]
 [-1.1538894]
 [-4.5924525]]
Output layer biases (1,) :
 [-0.49733716]