Skorch is a scikit-learn compatible wrapper. So if you will feel comfortable using it, if you’re using scikit-learn a lot or like it’s API.
On the other hand, Ignite let’s you define your model and training procedure and just provides some callbacks etc. for convenience. It sounds interesting.
I cannot recommend any wrapper so far, since I’m using plain Pytorch.
For me it’s the right abstraction, so that I can easily define my nets and try some crazy idea.
Using learning rate schedulers etc. I have everything I need so far.
The only point I would like to have is a smoother Visdom integration. At the moment I feel like creating a lot of boilerplate code to visualize the loss etc., but that’s a Visdom issue. 
Give both wrappers a shot and post your experience.