Implementation of deep learning in pennylane

Inspired by the quanvolutional Neural Network example in pennylane, whats the limitation of implementing deep learning algorithms in pennylane.For example DNN with 2 hidden layers and Back Propagation.

Hi @Umair_Ali_Khan, welcome to the Forum!

The limitation is mostly that you will be running a simulator on a classical computer, and at some point you will probably run out of memory. Usually this happens at around 20 qubits for a standard laptop. Depending on the interface that you’re using and the return type you may also find some limitations. You can see them here in the docs.

Please let me know if you have any further questions!