<p>One way to get weight decay in TensorFlow is by adding L2-regularization to the loss. This is equivalent to weight decay for standard SGD (but not for adaptive gradient optimizers) according to <a href="https://arxiv.org/pdf/1711.05101.pdf" rel="nofollow noreferrer">Decoupled Weight Decay Regularization</a> paper by Loshchilov &amp; Hutter.</p>
SGD with weight decay parameter in tensorflow
<p>In Keras and Pytorch, the SGD optimizer have Weight Decay parameter.I found <strong>tf.train.GradientDescentOptimizer</strong> do not have weight decay parameter. What is the tensorflow equivalent of SGD with weight decay? </p>

<p>Pytorch Optim - <a href="https://pytorch.org/docs/stable/optim.html" rel="nofollow noreferrer">https://pytorch.org/docs/stable/optim.html</a></p>

<p>Keras Optimizer - <a href="https://keras.io/optimizers/" rel="nofollow noreferrer">https://keras.io/optimizers/</a></p>