(x)
return tf.reduce_mean(tf.sqrt(var + 1e-6))
Computes the standard deviation average.

  This is used by the discriminator as a form of batch discrimination.

  Args:
    x: A `Tensor` for which to compute the standard deviation average. The first
        dimension must be batch size.

  Returns:
    A scalar `Tensor` which is the mean variance of variable x.
Computes the standard deviation average.
Computes the standard deviation average .
def minibatch_mean_stddev(x):
  """Computes the standard deviation average.

  This is used by the discriminator as a form of batch discrimination.

  Args:
    x: A `Tensor` for which to compute the standard deviation average. The first
        dimension must be batch size.

  Returns:
    A scalar `Tensor` which is the mean variance of variable x.
  """
  mean, var = tf.nn.moments(x, axes=[0])
  del mean
  return tf.reduce_mean(tf.sqrt(var + 1e-6))
def minibatch_mean_stddev ( x ) : mean , var = tf . nn . moments ( x , axes = [ 0 ] ) del mean return tf . reduce_mean ( tf . sqrt ( var + 1e-6 ) )