title: How is kernel size in keras convolution layers defined?
body: <p>According to the documentation website (<a href="https://keras.io/layers/convolutional/" rel="nofollow noreferrer">https://keras.io/layers/convolutional/</a>) the kernel size of a keras convolution layer is defined as <strong>height x width</strong>:</p>
  
  <blockquote>
    <p>kernel_size: An integer or tuple/list of 2 integers, specifying the
    height and width of the 2D convolution window. Can be a single integer
    to specify the same value for all spatial dimensions.</p>
  </blockquote>
  
  <p>In the code documentation however it is defined as the exact opposite:</p>
  
  <blockquote>
    <p>kernel_size: An integer or tuple/list of 2 integers, specifying the
                width and height of the 2D convolution window.
                Can be a single integer to specify the same value for
                all spatial dimensions.</p>
  </blockquote>
  
  <p>Which one is true? As far as I figured out, the definition of the website should be the right one, am i right?</p>