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class WScaleConv2DLayer(KL.Conv2D):
    def __init__(self, *args, **kwargs):               
        kwargs['kernel_initializer'] = keras.initializers.random_normal()
        
        super(WScaleConv2DLayer,self).__init__(*args,**kwargs)
    def build(self, input_shape):
        super().build(input_shape)
        kernel_shape = K.int_shape(self.kernel)
        std = np.sqrt(2) / np.sqrt( np.prod(kernel_shape[:-1]) )
        self.wscale = K.constant(std, dtype=K.floatx() )
    def call(self, input, **kwargs):
        k = self.kernel                        
        self.kernel = self.kernel*self.wscale
        x = super().call(input,**kwargs)
        self.kernel = k                        
        return x