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)