Using multiple worker s(num_workers > 0) for loading the data with DataLoader, results in a strange behavior. Here is a sample code snippet:
import xarray as xr
class mydataset(torch.utils.data.Dataset):
    def __init__(self,datapath):
        self.ds = xr.open_dataset(datapath)
        self.labels = # read the lables from some dimensions of self.ds
    def __len__(self):
        return len(self.labels)

    def __getitem__(self, idx):
        return #choose some value from the dimensions of self.ds



Using this method for loading the data I face NaNs or very extreme values which are not expected at all. There is another issue 17 which might be also related.