<p dir="auto">I am going to use loss information to update learning rate at each epoch by the following formula:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="             learning_rate = initial_learning_rate * exp(Loss)"><pre class="notranslate"><code class="notranslate">             learning_rate = initial_learning_rate * exp(Loss)
</code></pre></div>
<p dir="auto">How to get the loss at each epoch and then implement the above updating law? Thanks!</p>
<p dir="auto">I have large number of models (of different structure) that were built using the same input shape (but not the same InputLayer object).<br>
Is it possible to merge their input into one of the same dimension?<br>
I know I can do<br>
m = Model(inputs=[m.input for m in models], output=....<br>
But this approach requires duplication the x variable in fit method. I would like to avoid this as the number of models is very large.</p>
<p dir="auto">Thanks</p>