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File "UAI1_full_resolution.py", line 278, in
out = model(batch)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "UAI1_full_resolution.py", line 36, in forward
x = F.relu(self.conv1(x, edge_index, edge_attr))
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/root/graph-pde-master/graph-neural-operator/nn_conv.py", line 271, in forward
return self.propagate(edge_index, x=x, pseudo=pseudo)
File "/root/miniconda3/lib/python3.8/site-packages/torch_geometric/nn/conv/message_passing.py", line 317, in propagate
out = self.message(**msg_kwargs)
File "/root/graph-pde-master/graph-neural-operator/nn_conv.py", line 274, in message
weight = self.nn(pseudo).view(-1, self.in_channels, self.out_channels)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/root/graph-pde-master/graph-neural-operator/utilities.py", line 226, in forward
x = l(x)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/activation.py", line 98, in forward
return F.relu(input, inplace=self.inplace)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/functional.py", line 1442, in relu
result = torch.relu(input)
RuntimeError: CUDA out of memory. Tried to allocate 1.44 GiB (GPU 0; 23.70 GiB total capacity; 20.41 GiB already allocated; 18.56 MiB free; 21.69 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
We implement the code on Cloud Platform and the cost of GPU exceeds 24GiB, so could you tell us the capacity of your GPU?
The text was updated successfully, but these errors were encountered:
File "UAI1_full_resolution.py", line 278, in
out = model(batch)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "UAI1_full_resolution.py", line 36, in forward
x = F.relu(self.conv1(x, edge_index, edge_attr))
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/root/graph-pde-master/graph-neural-operator/nn_conv.py", line 271, in forward
return self.propagate(edge_index, x=x, pseudo=pseudo)
File "/root/miniconda3/lib/python3.8/site-packages/torch_geometric/nn/conv/message_passing.py", line 317, in propagate
out = self.message(**msg_kwargs)
File "/root/graph-pde-master/graph-neural-operator/nn_conv.py", line 274, in message
weight = self.nn(pseudo).view(-1, self.in_channels, self.out_channels)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/root/graph-pde-master/graph-neural-operator/utilities.py", line 226, in forward
x = l(x)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/activation.py", line 98, in forward
return F.relu(input, inplace=self.inplace)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/functional.py", line 1442, in relu
result = torch.relu(input)
RuntimeError: CUDA out of memory. Tried to allocate 1.44 GiB (GPU 0; 23.70 GiB total capacity; 20.41 GiB already allocated; 18.56 MiB free; 21.69 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
We implement the code on Cloud Platform and the cost of GPU exceeds 24GiB, so could you tell us the capacity of your GPU?
The text was updated successfully, but these errors were encountered: