Can a quantum generator in Hybrid GAN generate RGB images? The generator is quantum, and the discriminator is classical.
The basic example of GAN is DCGAN Tutorial — PyTorch Tutorials 2.0.0+cu117 documentation
and for QGAN is Quantum GANs — PennyLane documentation
I just need a quantum generator for the data used in the DCGAN tutorial. How to achieve it?
You can create hybrid PyTorch-PennyLane models with
qml.qnn.TorchLayer. Here is an example where it’s used: Turning quantum nodes into Torch Layers — PennyLane documentation
For your application — a quantum generator and a classical discriminator — the QGAN demo you linked in your post and the demo I linked above should be enough to get started!
Can we also interface with Convolutional layers other than Linear layers, as shown in your demo: Turning quantum nodes into Torch Layers — PennyLane documentation ?
Yep — interfacing with PyTorch isn’t limited to certain layer types, activation functions, etc. Mix and match to your heart’s content!