def print_act_stats()

in tfops.py [0:0]


def print_act_stats(x, _str=""):
    if not do_print_act_stats:
        return x
    if hvd.rank() != 0:
        return x
    if len(x.get_shape()) == 1:
        x_mean, x_var = tf.nn.moments(x, [0], keep_dims=True)
    if len(x.get_shape()) == 2:
        x_mean, x_var = tf.nn.moments(x, [0], keep_dims=True)
    if len(x.get_shape()) == 4:
        x_mean, x_var = tf.nn.moments(x, [0, 1, 2], keep_dims=True)
    stats = [tf.reduce_min(x_mean), tf.reduce_mean(x_mean), tf.reduce_max(x_mean),
             tf.reduce_min(tf.sqrt(x_var)), tf.reduce_mean(tf.sqrt(x_var)), tf.reduce_max(tf.sqrt(x_var))]
    return tf.Print(x, stats, "["+_str+"] "+x.name)