title: Get output from a non final keras model layer
body: <p>I am using ubuntu with python 3 and keras over tensorflow, I am trying to create a model using transfer learning from a pre trained keras model as explained <a href="https://www.learnopencv.com/keras-tutorial-transfer-learning-using-pre-trained-models/" rel="noreferrer">here</a>: </p>
  
  <p>I am using the following code </p>
  
  <pre><code>import numpy as np
  from keras.applications import vgg16, inception_v3, resnet50, mobilenet
  from keras import Model
  
  a = np.random.rand(1, 224, 224, 3) + 0.001
  a = mobilenet.preprocess_input(a)
  
  mobilenet_model = mobilenet.MobileNet(weights='imagenet')
  
  mobilenet_model.summary()
  inputLayer = mobilenet_model.input
  
  m = Model(input=inputLayer, outputs=mobilenet_model.get_layer("conv_pw_13_relu")(inputLayer))
  m.set_weights(mobilenet_model.get_weights()[:len(m.get_weights())])
  p = m.predict(a)
  print(np.std(p), np.mean(p))
  print(p.shape)
  </code></pre>
  
  <p>The output of the layer I am using is always an array of zeros, Should I load the weight to p that i am creating in order for the pre trained model to actually work?</p>