Is there a better way to split data and deal with an unbalanced dataset?

[pevogam (Plamen Dimitrov)]

I think some solutions to this question have already been proposed here:

DataLoader - using SubsetRandomSampler and WeightedRandomSampler at the same time

I have a dataset that contains both the training and validation set. I am aware that I can use the SubsetRandomSampler to split the dataset into the training and validation subsets. The dataset however, has an unbalanced class ratio. How can I also use the WeightedRandomSampler together with the SubsetRandomSampler ? Below is what I currently have using only the SubsetRandomSampler. # build the dataset dset = TrajectoryDataset( path, obs_len=args.obs_len, skip=ar…