Get the output of each layer in Neural network

Lets Consider following simple neural network

import keras.backend as K

from keras.models import Model
from keras.layers import Input, Dense

input_layer = Input((10,))

layer_1 = Dense(10)(input_layer)
layer_2 = Dense(20)(layer_1)
layer_3 = Dense(5)(layer_2)

output_layer = Dense(1)(layer_3)

model = Model(inputs=input_layer, outputs=output_layer)

# some random input
import numpy as np
features = np.random.rand(100,10)

and consider this model is trained

# With a Keras function get the ouputs of all the layers
get_all_layer_outputs = K.function([model.layers[0].input],
                                  [l.output for l in model.layers[0:]])

layer_output = get_all_layer_outputs([features]) # return the same thing

#layer_output is a list of all layers outputs

#if the model is trained you will get the output for input with trained weights other wise 
it will give outout with initial weights