dacd89544ddaf1ab7e572850ebdec3dbaeda0ea0,autokeras/layer_transformer.py,,deeper_conv_block,#Any#Any#,8

Before Change

                               kernel_size=filter_shape,
                               padding="same")
    new_conv_layer.build((None,) * (len(filter_shape) + 1) + (n_filters,))
    new_conv_layer.set_weights((weight, bias))
    return [new_conv_layer,
            BatchNormalization(),
            Activation("relu")]

After Change

                               kernel_size=filter_shape,
                               padding="same")
    new_conv_layer.build((None,) * (len(filter_shape) + 1) + (n_filters,))
    new_conv_layer.set_weights((add_noise(weight, np.array([0, 1])), add_noise(bias, np.array([0, 1]))))
    return [new_conv_layer,
            BatchNormalization(),
            Activation("relu")]

Instances