arams) {
    logPrior =<span class="st"> </span>-<span class="st"> </span>(tf$<span class="kw">reduce_sum</span>(tf$<span class="kw">abs</span>(params$beta)) +<span class="st"> </span>tf$<span class="kw">reduce_sum</span>(tf$<span class="kw">abs</span>(params$bias)))
    <span class="kw">return</span>(logPrior)
}</code></pre></div>
<p>Finally, we’ll set the stepsize parameters for the algorithm, along with the minibatch size. <code>sgldcv</code> relies on two stepsize parameters, one for the optimization 