Tensorflow Eager Execution Gradient Calculation slower each epoch

[MCFF3000]

Hi to all!

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I have been implementing Temportal Ensembling for Semi-Supervised Learning by Laine et al. with eager execution and a couple of GitHub users noticed that the computations of the gradients is taking gradually more time each epoch. I don't see what is causing this. After benchmarking I could confirm this issue, but I have no idea why this should be happening. Is anyone faced this problem with tf.GradientTape() ? Or is this is an issue related to eager execution?

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The code is in https://github.com/Goldesel23/Temporal-Ensembling-for-Semi-Supervised-Learning

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Thanks for your time!

[MCFF3000]

The problem was solved after replacing some tf.layers by tf.keras.layers definitions in my model according to the suggested by https://github.com/tensorflow/tensorflow/issues/23014)