When I implemented Smog.py and ran it until the 4th epoch, I encountered errors after setting self.n_groups = 300:
Traceback (most recent call last):
File "/datashare3/charis/code2/SSL-yolo8/lightly-master/examples/pytorch/smog_yolo.py", line 230, in
smogmodel.reset_group_features(memory_bank=memory_bank)
File "/datashare3/charis/code2/SSL-yolo8/lightly-master/examples/pytorch/smog_yolo.py", line 59, in reset_group_features
group_features = self._cluster_features(features.t())
File "/datashare3/charis/code2/SSL-yolo8/lightly-master/examples/pytorch/smog_yolo.py", line 51, in _cluster_features
kmeans = KMeans(self.n_groups).fit(features)
File "/datashare3/charis/anaconda/envs/yolov8SSL/lib/python3.9/site-packages/sklearn/base.py", line 1473, in wrapper
return fit_method(estimator, *args, **kwargs)
File "/datashare3/charis/anaconda/envs/yolov8SSL/lib/python3.9/site-packages/sklearn/cluster/_kmeans.py", line 1473, in fit
self._check_params_vs_input(X)
File "/datashare3/charis/anaconda/envs/yolov8SSL/lib/python3.9/site-packages/sklearn/cluster/_kmeans.py", line 1414, in _check_params_vs_input
super()._check_params_vs_input(X, default_n_init=10)
File "/datashare3/charis/anaconda/envs/yolov8SSL/lib/python3.9/site-packages/sklearn/cluster/_kmeans.py", line 878, in _check_params_vs_input
raise ValueError(
ValueError: n_samples=128 should be >= n_clusters=300.
After setting self.n_groups = 128, another error arose:
Traceback (most recent call last):
File "/datashare3/charis/code2/SSL-yolo8/lightly-master/examples/pytorch/smog_yolo.py", line 243, in
assignments = smogmodel.smog.assign_groups(x1_encoded)
File "/datashare3/charis/anaconda/envs/yolov8SSL/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "/datashare3/charis/code2/SSL-yolo8/lightly-master/lightly/models/modules/heads.py", line 401, in assign_groups
return torch.argmax(self.forward(x, self.group_features), dim=-1)
File "/datashare3/charis/code2/SSL-yolo8/lightly-master/lightly/models/modules/heads.py", line 362, in forward
logits = torch.mm(x, group_features.t())
RuntimeError: mat1 and mat2 shapes cannot be multiplied (256x128 and 76800x128).
Hi, could you share the relevant code?
It looks like the memory bank features need to be transposed. The shapes should be 256x128 and 128x76800. You can transpose them by setting MemoryBank(feature_dim_first=False) or feature_dim_first=True depending on your code.
lightly-ai
