title: How to code a residual block using two layers of a basic CNN algorithm built with "tensorflow.keras"?
body: <p>I have a basic CNN model's code built with <strong>tensorflow.keras</strong> library:</p>
  <pre><code>model = Sequential()
  
  # First Layer
  model.add(Conv2D(64, (3,3), input_shape = (IMG_SIZE,IMG_SIZE,1)))
  model.add(Activation(&quot;relu&quot;))
  model.add(MaxPooling2D(pool_size = (3,3)))
  
  # Second Layer
  model.add(Conv2D(64, (3,3)))
  model.add(Activation(&quot;relu&quot;))
  model.add(MaxPooling2D(pool_size = (3,3)))
  
  # Third Layer
  model.add(Conv2D(64, (3,3)))
  model.add(Activation(&quot;relu&quot;))
  model.add(MaxPooling2D(pool_size = (3,3)))
  
  # Fourth Layer
  model.add(Conv2D(64, (3,3)))
  model.add(Activation(&quot;relu&quot;))
  model.add(MaxPooling2D(pool_size = (3,3)))
  
  # Fifth Layer
  model.add(Conv2D(64, (3,3)))
  model.add(Activation(&quot;relu&quot;))
  model.add(MaxPooling2D(pool_size = (3,3)))
  
  model.add(Flatten())
  
  # Sixth Layer
  model.add(Dense(64))
  model.add(Activation(&quot;relu&quot;))
  
  # Seventh Layer
  model.add(Dense(1))
  model.add(Activation('sigmoid'))
  </code></pre>
  <p>Now, I want to make a connection between the <strong>second</strong> and the <strong>fourth</strong> layer to achieve a <strong>residual block</strong> using <strong>tensorflow.keras</strong> library.</p>
  <p>So, How should I modify the code to achieve such a <strong>residual block</strong>?</p>