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Using Ubuntu Deepstack docker 2022.01.1 on esxi with grid Nvidia GPU. RTX A5000
After sometime Deepstack seems to crash with:
File "/app/intelligencelayer/shared/detection.py", line 81, in run_task
det = detector.predict(img_path, threshold)
File "/app/intelligencelayer/shared/./process.py", line 63, in predict
pred = self.model(img, augment=False)[0]
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/app/intelligencelayer/shared/./models/yolo.py", line 149, in forward
return self.forward_once(x, profile) # single-scale inference, train
File "/app/intelligencelayer/shared/./models/yolo.py", line 176, in forward_once
x = m(x) # run
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/app/intelligencelayer/shared/./models/yolo.py", line 75, in forward
y[..., 0:2] * 2.0 - 0.5 + self.grid[i].to(x[i].device)
RuntimeError: The size of tensor a (32) must match the size of tensor b (40) at non-singleton dimension 2
Anyway increase logging level to get timestamps?
Anyone have an idea what’s causing this crash?
Any options to catch this and restart deepstack docker instance automatically?
The text was updated successfully, but these errors were encountered:
Hi @babbahotep, this error is as a result of shape mismatch. I'd suggest you make sure the shape of both input tensors match, so in place addition can be executed hitch free.
Using Ubuntu Deepstack docker 2022.01.1 on esxi with grid Nvidia GPU. RTX A5000
After sometime Deepstack seems to crash with:
File "/app/intelligencelayer/shared/detection.py", line 81, in run_task
det = detector.predict(img_path, threshold)
File "/app/intelligencelayer/shared/./process.py", line 63, in predict
pred = self.model(img, augment=False)[0]
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/app/intelligencelayer/shared/./models/yolo.py", line 149, in forward
return self.forward_once(x, profile) # single-scale inference, train
File "/app/intelligencelayer/shared/./models/yolo.py", line 176, in forward_once
x = m(x) # run
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/app/intelligencelayer/shared/./models/yolo.py", line 75, in forward
y[..., 0:2] * 2.0 - 0.5 + self.grid[i].to(x[i].device)
RuntimeError: The size of tensor a (32) must match the size of tensor b (40) at non-singleton dimension 2
Anyway increase logging level to get timestamps?
Anyone have an idea what’s causing this crash?
Any options to catch this and restart deepstack docker instance automatically?
The text was updated successfully, but these errors were encountered: