sjunhongshen / orca Goto Github PK

When I run cifar100 with Docker, it stops after print the src feat shape torch.Size([5000, 128]) torch.Size([5000]) num classes 100. (It did not stop, but it ran for a long time in this part still did not end)
I read the code, and find that the problem is in creating subsets.
def load_by_class(loader, num_classes):
if len(train_set.getitem(0)) == 3:
try:
subsets = {target: torch.utils.data.Subset(train_set, [i for i, (x, y, _) in enumerate(train_set) if y == target]) for target in range(num_classes)}
except:
subsets = {target: torch.utils.data.Subset(train_set, [i for i, (x, y, _) in enumerate(train_set) if y.item() == target]) for target in range(num_classes)}
else:
try:
subsets = {target: torch.utils.data.Subset(train_set, [i for i, (x, y) in enumerate(train_set) if y == target]) for target in range(num_classes)}
Do u know what causes the issue?
And I change the implementation of this part. I can pass this part, but I got this.
BrokenPipeError: [Errno 32] Broken pipe
Traceback (most recent call last):
File "/opt/conda/lib/python3.8/multiprocessing/queues.py", line 245, in _feed
send_bytes(obj)
File "/opt/conda/lib/python3.8/multiprocessing/connection.py", line 200, in send_bytes
self._send_bytes(m[offset:offset + size])
File "/opt/conda/lib/python3.8/multiprocessing/connection.py", line 411, in _send_bytes
self._send(header + buf)
File "/opt/conda/lib/python3.8/multiprocessing/connection.py", line 368, in _send
n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe

Another information: It show me that ot.gpu not found - coupling computation will be in cpu.