30dfa316d689a232c2e6deaa813827be52aba961,niftynet/network/simulator_gan.py,ImageGenerator,layer_op,#ImageGenerator#Any#Any#Any#Any#,35

Before Change

        conditioning_channels = conditioning.get_shape().as_list()[
                                    -1] + add_noise if conditioning is not None else add_noise

        w_init = self.initializers["w"]
        b_init = self.initializers["b"]
        ch = [512]
        sz = [image_size[:-1]]
        keep_prob_ph = 1  // not passed in as a placeholder

After Change

            if add_noise:
                feature_shape = g_h5.get_shape().as_list()[0:-1]
                noise_shape = feature_shape + [add_noise]
                noise = tf.random_normal(noise_shape, 0, .1)
                g_h5 = tf.concat([g_h5, noise], axis=3)
            conv_layer = ConvolutionalLayer(
                n_output_chns=1,
                kernel_size=3,

Instances