How To Switch From Keras Tensortype To Numpy Array For A Custom Layer?

So I have a custom layer, that does not have any weights. In a fist step, I tried to implement the functions manipulating the input tensors in Kers. But I did not succeed because

Solution 1:

As mentioned by Daniel Möller in the comments, Keras needs to be able to backpropagate through your layer, in order the calculate the gradients for the previous layers. Your layer needs to be differentiable for this reason.

For the same reason you can only use Keras operations, as those can be automatically differentiated with autograd. If your layer is something simple, have a look at the Lambda layer where you can implement custom layers quickly.

As an aside, Keras backend functions should cover a lot of use cases, so if you're stuck with writing your layer through those, you might want to post a another question here.

Hope this helps.