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]. 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.