Get Gate Activation of GRU-Cells in TensorFlow
I am trying to figure out the same problem as well. I don't have the full solution but maybe we can help each other out. 

If you do: names =[n.name for n in tf.get_default_graph().as_graph_def().node]

This will give you a list of all the names of the nodes in the graph. For Rnn the out put for names should look some what like this

.
'RNN/Shape',
'RNN/strided_slice/stack',
'RNN/strided_slice/stack_1',
.
. 
.
'RNN/transpose'
.


Then you can use get_operation_by_name to get the operation you want to look at. 

 rnn_transpose=tf.get_default_graph().get_operation_by_name('RNN/transpose').outputs[0]


From that you can run the eval() with your regular sess and feed_dict

 rnn_transpose.eval(session=sess,feed_dict =feed_dict)


The problem here is now we have to find which operations in the graph correspond to the proper gate operations.