I want to break a dataset into two subsets, and eventually one dataloader for each subset. I searched on the forum and found some related posts such as [ Torch.utils.data.dataset.random_split 2]. I tried random_split(), but still got errors:
train_dataset, test_dataset = torch.utils.data.random_split(fullDataSet, [train_size, test_size])  
training_loader = DataLoader(train_dataset, batch_size = batch_size, shuffle=True, num_workers=8) 
test_loader = DataLoader(test_dataset, batch_size = batch_size, shuffle=True, num_workers=8) 

for j, data in enumerate(training_loader):
    signals, labels = data
    if j%100 == 0: 
        print(labels)


RuntimeError                              Traceback (most recent call last)
 in 
----> 1 for j, data in enumerate(training_loader):
2     signals, labels = data
3     if j%100 == 0:
4         print(labels)
…
RuntimeError: CUDA error: initialization error
Thanks.