Using tf.trainable_variables() to show names of trainable variables

Question

I'm dealing with weights in a RNNCell.

I have the following code

var_names = []    
for var in tf.trainable_variables():    
    var_names.append(var.name)

In another file called model.py, I am printing the names of the trainable variables just appended to var_names. However, I find that the "name" attribute of the trainable variables is not useful because not very descriptive.

Do the weights of an RNNcell have names?

If that's useful, here's another possibly relevant piece of code:

cell_fn = tf.nn.rnn_cell.GRUCell   
rnn_fw_1 = cell_fn(num_hidden_1, **additional_cell_args)    
rnn_fw_1 = tf.nn.rnn_cell.DropoutWrapper(rnn_fw_1, input_keep_prob=keep_prob_1)

Answer 1

Try this:

variables_names = [v.name for v in tf.trainable_variables()]
values = sess.run(variables_names)
for k, v in zip(variables_names, values):
    print "Variable: ", k
    print "Shape: ", v.shape
    print v