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We found that the memory usage of the baseline is different on different OS. It exceeds the limit (about 3400MB) on Ubuntu20.04, but not on Ubuntu22.04. Additionally, we found that this seems to be caused by PyTorch.
Here is the result of memory-profiler's analysis on the forward function of the model.
Line # Mem usage Increment Occurrences Line Contents
=============================================================
71 2240.7 MiB 2240.7 MiB 1 @profile
72 def forward(self, x):
73 2240.7 MiB 0.0 MiB 1 bsz = x.size(0)
74 3247.5 MiB 1006.9 MiB 1 out = relu(self.bn1(self.conv1(x.view(bsz, 3, 32, 32))))
75 3248.5 MiB 1.0 MiB 1 out = self.layer1(out)
76 3248.7 MiB 0.1 MiB 1 out = self.layer2(out)
77 3248.7 MiB 0.0 MiB 1 out = self.layer3(out)
78 3248.7 MiB 0.0 MiB 1 out = self.layer4(out)
79 3248.7 MiB 0.0 MiB 1 out = avg_pool2d(out, 4)
80 3248.7 MiB 0.0 MiB 1 out = out.view(out.size(0), -1)
81 3249.2 MiB 0.6 MiB 1 out = self.linear(out)
82 3249.2 MiB 0.0 MiB 1 return out
The text was updated successfully, but these errors were encountered:
Hi @dwh649821599 . Thanks for reporting the issue. This was an unexpected behavior. It seems like the difference should be around 200-300 MBs in different environments. The max RAM limit is now increased to 4000. The should be high enough for different environments.
We found that the memory usage of the baseline is different on different OS. It exceeds the limit (about 3400MB) on Ubuntu20.04, but not on Ubuntu22.04. Additionally, we found that this seems to be caused by PyTorch.
Here is the result of
memory-profiler
's analysis on theforward
function of the model.The text was updated successfully, but these errors were encountered: