melodyguan / enas

TensorFlow Code for paper "Efficient Neural Architecture Search via Parameter Sharing"

Home Page:https://arxiv.org/abs/1802.03268

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Longer training time for each batch after some steps

SiZuo opened this issue · comments

commented

Hi,
I found that the training time of each step is getting slower during the training phase. It might because there are some new operations added to the graph after sess.run().

I am thinking to use some command to fix the graph like:
tf.reset_default_graph()
sess.get_default_graph.finalize()

But my question is that the network structure is changing after searching a new architecture by the controller, so will the command above be a problem?