e4ee8e989f0ee8138798c290233c1c3ec7d3fb61,lib/gan.py,,generator,#Any#Any#Any#,9

Before Change

        //noise = tf.random_uniform(new_shape,-1, 1, dtype=config["dtype"])
        //net = tf.concat(3, [net,noise])

        net = conv2d(net, z_proj_dims, name="g_conv_proj", k_w=1, k_h=1, d_h=1, d_w=1)
        print("Generator created conv layer:", net)

        net = tf.reshape(net, [config["batch_size"],1,1,z_proj_dims])

After Change

        gz = int(net.get_shape()[1])
        net = linear(net, z_proj_dims*primes[0]*primes[1], scope="g_lin_proj")
        new_shape = [config["batch_size"], primes[0],primes[1],z_proj_dims]
        net = tf.reshape(net, new_shape)

        //noise = tf.random_uniform(new_shape,-1, 1, dtype=config["dtype"])

Instances