There are a couple of reasons WHY you can get a NaN-result, often it is because of too high a learning rate but plenty other reasons are possible like for example corrupt data in your input-queue or a log of 0 calculation.
Anyhow, debugging with a print as you describe cannot be done by a simple print (as this would result only in the printing of the tensor-information inside the graph and not print any actual values).
However, if you use tf.print as an op in bulding the graph (tf.print) then when the graph gets executed you will get the actual values printed (and it IS a good exercise to watch these values to debug and understand the behavior of your net).
However, you are using the print-statement not entirely in the correct manner. This is an op, so you need to pass it a tensor and request a result-tensor that you need to work with later on in the executing graph. Otherwise the op is not going to be executed and no printing occurs. Try this:
Z = tf.sqrt(Delta_tilde)
Z = tf.Print(Z,[Z], message="my Z-values:") # <-------- TF PRINT STATMENT
Z = Transform(Z) # potentially some transform, currently I have it to return Z for debugging (the identity)
Z = tf.pow(Z, 2.0)