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I am trying to run the program on a ubnutu 20.4 machine with GTX1650Ti GPU, but face lack of memory issue.
Does this module have any low mem option i.e like reduce channel option with less memory requirement.
Or any other work around possible?
python3 test.py --input_dir inputimg --output_dir outputimg --device cuda
model loaded: ./weights/paprika.pt
Traceback (most recent call last):
File "test.py", line 92, in
test(args)
File "test.py", line 48, in test
out = net(image.to(device), args.upsample_align).cpu()
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/anime/animagen-pytorch-mur/animegan2-pytorch/model.py", line 91, in forward
out = self.block_a(input)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/container.py", line 117, in forward
input = module(input)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/container.py", line 117, in forward
input = module(input)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 423, in forward
return self._conv_forward(input, self.weight)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 419, in _conv_forward
return F.conv2d(input, weight, self.bias, self.stride,
RuntimeError: CUDA out of memory. Tried to allocate 7.96 GiB (GPU 0; 3.82 GiB total capacity; 2.07 GiB already allocated; 549.38 MiB free; 2.09 GiB reserved in total by PyTorch)
The text was updated successfully, but these errors were encountered:
Hi,
I am trying to run the program on a ubnutu 20.4 machine with GTX1650Ti GPU, but face lack of memory issue.
Does this module have any low mem option i.e like reduce channel option with less memory requirement.
Or any other work around possible?
python3 test.py --input_dir inputimg --output_dir outputimg --device cuda
model loaded: ./weights/paprika.pt
Traceback (most recent call last):
File "test.py", line 92, in
test(args)
File "test.py", line 48, in test
out = net(image.to(device), args.upsample_align).cpu()
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/anime/animagen-pytorch-mur/animegan2-pytorch/model.py", line 91, in forward
out = self.block_a(input)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/container.py", line 117, in forward
input = module(input)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/container.py", line 117, in forward
input = module(input)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 423, in forward
return self._conv_forward(input, self.weight)
File "/home/murugan86/.local/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 419, in _conv_forward
return F.conv2d(input, weight, self.bias, self.stride,
RuntimeError: CUDA out of memory. Tried to allocate 7.96 GiB (GPU 0; 3.82 GiB total capacity; 2.07 GiB already allocated; 549.38 MiB free; 2.09 GiB reserved in total by PyTorch)
The text was updated successfully, but these errors were encountered: