`Traceback (most recent call last):


 "/home/cbird/work/net/sy_psm/finetune.py", line 201, in <module>

main()


 "/home/cbird/work/net/sy_psm/finetune.py", line 176, in main

test_loss = test(imgL, imgR, disp_L)


 "/home/cbird/work/net/sy_psm/finetune.py", line 127, in test

output3 = model(imgL, imgR)


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

result = self.forward(*input, **kwargs)


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/parallel/data_parallel.py", line 150, in forward

return self.module(*inputs[0], **kwargs[0])


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

result = self.forward(*input, **kwargs)


 "/home/cbird/work/net/sy_psm/models/stackhourglass.py", line 133, in forward

out2, pre2, post2 = self.dres3(out1, pre1, post1)


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

result = self.forward(*input, **kwargs)


 "/home/cbird/work/net/sy_psm/models/stackhourglass.py", line 53, in forward

out = self.conv6(post)
# in:1/8 out:1/4


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

result = self.forward(*input, **kwargs)


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/modules/container.py", line 92, in forward

input = module(input)


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

result = self.forward(*input, **kwargs)


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/modules/batchnorm.py", line 83, in forward

exponential_average_factor, self.eps)


 "/home/cbird/anaconda3/envs/lhx/lib/python2.7/site-packages/torch/nn/functional.py", line 1697, in batch_norm

training, momentum, eps, torch.backends.cudnn.enabled
RuntimeError: CUDA out of memory. Tried to allocate 1.30 GiB (GPU 0; 10.91 GiB total capacity; 8.06 GiB already allocated; 508.50 MiB free; 1.33 GiB cached)`

Traceback (most recent call last):


 "extract.py", line 157, in <module>

main()


 "extract.py", line 87, in main

extract(data_loader, model, path_file, args.mode)


 "extract.py", line 121, in extract

output_att = model(input_var)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/modules/module.py", line 206, in __call__

result = self.forward(*input, **kwargs)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 61, in forward

outputs = self.parallel_apply(replicas, inputs, kwargs)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 71, in parallel_apply

return parallel_apply(replicas, inputs, kwargs)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 46, in parallel_apply

raise output


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 25, in _worker

output = module(*input, **kwargs)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/modules/module.py", line 206, in __call__

result = self.forward(*input, **kwargs)


 "/home/aosman/vqa/vqa.pytorch/vqa/models/convnets.py", line 62, in <lambda>

model.forward = lambda x: forward_resnet(convnet, x)


 "/home/aosman/vqa/vqa.pytorch/vqa/models/convnets.py", line 26, in forward_resnet

x = self.conv1(x)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/modules/module.py", line 206, in __call__

result = self.forward(*input, **kwargs)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 237, in forward

self.padding, self.dilation, self.groups)


 "/home/aosman/miniconda2/envs/vqa/lib/python3.6/site-packages/torch/nn/functional.py", line 40, in conv2d

return f(input, weight, bias)
RuntimeError: tensors are on different GPUs
