Function conv_spectral_norm

train_code/layers.py:55–62

(x, channel, k_size, stride=1, name='conv_snorm')

def conv_spectral_norm(x, channel, k_size, stride=1, name='conv_snorm'):
    with tf.variable_scope(name):
        w = tf.get_variable("kernel", shape=[k_size[0], k_size[1], x.get_shape()[-1], channel])
        b = tf.get_variable("bias", [channel], initializer=tf.constant_initializer(0.0))

        x = tf.nn.conv2d(input=x, filter=spectral_norm(w), strides=[1, stride, stride, 1], padding='SAME') + b

        return x