title: Keras: What is model.inputs in VGG16
body: <p>I start playing with keras and vgg16 recently, and I am using keras.applications.vgg16. </p>
  
  <p>But here I come with a question about what is <code>model.inputs</code> because I saw others using it in <a href="https://github.com/keras-team/keras/blob/master/examples/conv_filter_visualization.py" rel="nofollow noreferrer">https://github.com/keras-team/keras/blob/master/examples/conv_filter_visualization.py</a> although it does not initialize it</p>
  
  <pre><code>    ...
      input_img = model.input
      ...
      layer_output = layer_dict[layer_name].output
      if K.image_data_format() == 'channels_first':
          loss = K.mean(layer_output[:, filter_index, :, :])
      else:
          loss = K.mean(layer_output[:, :, :, filter_index])
  
      # we compute the gradient of the input picture wrt this loss
      grads = K.gradients(loss, input_img)[0]
  </code></pre>
  
  <p>I checked the keras site but it only said that is an input tensor with shape (1,224,224,3) But I still don't understand what is that exactly. Is that an image from ImageNet?Or a default image provided by keras for keras model?</p>
  
  <p>I am sorry if I don't have enough understanding of deep learning, but can someone explain it to me please. Thanks</p>