3159bd786503bf40f622c66d5044970bbee50b02,hypergan/generators/resize_conv.py,,generator,#Any#Any#,5

Before Change

        net = block_conv(net, activation, batch_size, "identity", "g_layers_"+str(i), output_channels=layers, filter=fltr, batch_norm=batch_norm, noise_shape=noise)
        if(net.get_shape()[3] != 3):
            // TODO: shared amongst generators?  Hide behind config?
            reshaped_z_proj = tf.reshape(z_proj, [config["batch_size"], resized_wh[0], resized_wh[1], -1])
            net = tf.concat(3, [net, reshaped_z_proj])

        if(i == depth-1):

After Change

            noise = [s[0],resized_wh[0],resized_wh[1],2**(depth-i)]
        else:
            noise = None
        net = tf.image.resize_images(net, [resized_wh[0], resized_wh[1]], 1)
        fltr = 3
        if fltr > net.get_shape()[1]:
            fltr=int(net.get_shape()[1])
        if fltr > net.get_shape()[2]:

Instances