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How to train on dataset with image size 384*384 #9

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angelowen opened this issue May 1, 2022 · 4 comments
Open

How to train on dataset with image size 384*384 #9

angelowen opened this issue May 1, 2022 · 4 comments

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@angelowen
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Hi, Edward.
Thanks a lot for your excellent work.
I met this problem when I run the code using my dataset with image size 384*384,
Any idea how to fix it?
/pytorch/aten/src/ATen/native/cuda/ScatterGatherKernel.cu:115: operator(): block: [2,0,0], thread: [32,0,0] Assertion idx_dim >= 0 && idx_dim < index_size && "index out of bounds" failed.
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/pytorch/aten/src/ATen/native/cuda/ScatterGatherKernel.cu:115: operator(): block: [0,0,0], thread: [31,0,0] Assertion idx_dim >= 0 && idx_dim < index_size && "index out of bounds" failed.
Traceback (most recent call last):
File "/home/jefflin/Documents/LoFGAN-pytorch/train.py", line 56, in
trainer.gen_update(imgs, label)
File "/home/jefflin/Documents/LoFGAN-pytorch/trainer.py", line 32, in gen_update
losses = self.model(xs, y, 'gen_update')
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/jefflin/Documents/LoFGAN-pytorch/networks/lofgan.py", line 31, in forward
feat_real, _, _ = self.dis(xs)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/jefflin/Documents/LoFGAN-pytorch/networks/lofgan.py", line 147, in forward
feat = self.cnn_f(x)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/container.py", line 139, in forward
input = module(input)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/jefflin/Documents/LoFGAN-pytorch/networks/blocks.py", line 198, in forward
x = self.conv(self.pad(x))
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1060, in call_impl
result = hook(self, input)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/utils/spectral_norm.py", line 105, in call
setattr(module, self.name, self.compute_weight(module, do_power_iteration=module.training))
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/utils/spectral_norm.py", line 85, in compute_weight
u = normalize(torch.mv(weight_mat, v), dim=0, eps=self.eps, out=u)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/functional.py", line 4431, in normalize
denom = input.norm(p, dim, keepdim=True).clamp_min(eps).expand_as(input)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/_tensor.py", line 417, in norm
return torch.norm(self, p, dim, keepdim, dtype=dtype)
File "/home/jefflin/.conda/envs/pytorch/lib/python3.9/site-packages/torch/functional.py", line 1356, in norm
return _VF.norm(input, p, _dim, keepdim=keepdim) # type: ignore[attr-defined]
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
@edward3862
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Hi, @angelowen. Is it a GPU memory problem or a code problem?

@angelowen
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I think it is a code problem, because it goes well when I train on image 128128 but break on image 6464.

@edward3862
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I'm cannot figure out this problem currently, since our experiment on VGGFace goes well with image size 64*64. Could you please check if the discriminator gets the right output given the same input as yours?

@llesky
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llesky commented Aug 3, 2022

I have the same issue. Any way to solve it?

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@edward3862 @llesky @angelowen