              kernel_size: kernel size of following convolution (5,5)
          '''
          self.stride = stride
          self.kernel_size = kernel_size
          super(ReflectionPadding2D, self).__init__(**kwargs)
  
      def build(self, input_shape):
          self.input_spec = [InputSpec(shape=input_shape)]
          super(ReflectionPadding2D, self).build(input_shape)
  
 
</s> remove         '''
        # Arguments
            stride: stride of following convolution (2)
            kernel_size: kernel size of following convolution (5,5)
        '''
 </s> add  </s> remove         super(ReflectionPadding2D, self).build(input_shape)
 </s> add         super().build(input_shape) </s> remove         """ If you are using "channels_last" configuration"""
 </s> add         """Computes the output shape of the layer.

        Assumes that the layer will be built to match that input shape provided.

        Parameters
        ----------
        input_shape: tuple or list of tuples
            Shape tuple (tuple of integers) or list of shape tuples (one per output tensor of the
            layer).  Shape tuples can include None for free dimensions, instead of an integer.

        Returns
        -------
        tuple
            An input shape tuple
        """ </s> remove class Scale(Layer):
    """
    GAN Custom Scal Layer
    Code borrows from https://github.com/flyyufelix/cnn_finetune
    """
    def __init__(self, weights=None, axis=-1, gamma_init='zero', **kwargs):
        self.axis = axis
        self.gamma = None
        self.gamma_init = initializers.get(gamma_init)
        self.initial_weights = weights
        super(Scale, self).__init__(**kwargs)

    def build(self, input_shape):
        self.input_spec = [InputSpec(shape=input_shape)]
 </s> add         The configuration of a layer does not include connectivity information, nor the layer
        class name. These are handled by `Network` (one layer of abstraction above).
        super().__init__(**kwargs)
              kernel_size: kernel size of following convolution (5,5)
          '''
          self.stride = stride
          self.kernel_size = kernel_size
        super().__init__(**kwargs)
  
      def build(self, input_shape):
          self.input_spec = [InputSpec(shape=input_shape)]
          super(ReflectionPadding2D, self).build(input_shape)
  
keep keep keep keep replace keep keep keep keep keep
 Simple backend unit tests (#1020)

* Add simple backend tests for lib.model
* Document lib.model
* Fix GMSD Loss for AMD
* Remove obsolete code from lib.model 
lib/model/layers.py