Why there is no difference in using batch_norm function when training and testing?

[JianqiangRen]

batch_norm(
inputs,
decay=0.999,
center=True,
scale=False,
epsilon=0.001,
activation_fn=None,
param_initializers=None,
param_regularizers=None,
updates_collections=tf.GraphKeys.UPDATE_OPS,
is_training=True,
reuse=None,
variables_collections=None,
outputs_collections=None,
trainable=True,
batch_weights=None,
fused=None,
data_format=DATA_FORMAT_NHWC,
zero_debias_moving_mean=False,
scope=None,
renorm=False,
renorm_clipping=None,
renorm_decay=0.99
)

parameters are listed above, and is_training should be true when model is under traing ,false when testing, but why there is no such difference in these codes?

[ppwwyyxx]

Answer is in the paper.