INNER CODE UNIT · Python

_instance_norm

aiff22/DPED · models.py:120

def _instance_norm(net):

    batch, rows, cols, channels = [i.value for i in net.get_shape()]
    var_shape = [channels]

    mu, sigma_sq = tf.compat.v1.nn.moments(net, [1,2], keepdims=True)
    shift = tf.Variable(tf.zeros(var_shape))
    scale = tf.Variable(tf.ones(var_shape))

    epsilon = 1e-3
    normalized = (net-mu)/(sigma_sq + epsilon)**(.5)

    return scale * normalized + shift


def _conv_init_vars(net, out_channels, filter_size, transpose=False):

    _, rows, cols, in_channels = [i.value for i in net.get_shape()]

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