Training Time and CPU Usage

Hello, Thank you so much for the excellent package on survival analysis.

I am using the DeepHit model, and I observed a weird thing: I have a dataset with input dimension over 200, and I can see it uses multiple CPUs at the same time when training. Then, I selected a subset of the training features which now I only have an input dimension of 6, but now the model is 3 times slower compared to the one with way more features, and I can see this time it does not uses multiple CPUs. I'm assuming it's about the number of workers in the fit function, but changing it does not affect anything. Do you have any insight about this?

Start by reproducing the reported DeepHit training comparison with input dimensions of over 200 versus 6, then inspect the fit function and its worker configuration. Compare CPU usage and training time in both cases; done requires explaining the difference or identifying a reproducible performance defect and its scope.

Written by the indexing model from the issue text.