v1.3 batch_norm layer

[sddi]

I use the batch norm layer like this:
`def batch_norm_layer(x,train_phase,scope_bn):

bn_train = batch_norm(x, decay=0.999, center=True, scale=True,
is_training=True,
reuse=None, # is this right?
trainable=True,
scope=scope_bn)
bn_inference = batch_norm(x, decay=0.999, center=True, scale=True,
is_training=False,
reuse=True, # is this right?
trainable=True,
scope=scope_bn)
z = tf.cond(train_phase, lambda: bn_train, lambda: bn_inference)
return z`

I don't know in v1.3.0 is the code worked?
I saw the issue1122, someone said it would not work well.

thank you in advance.

[drpngx]

This question is better asked on StackOverflow since it is not a bug or feature request. There is also a larger community that reads questions there. Thanks!