How to solve "out of memory"?

[fu123456]

Hi,
My GPU memory is enough, 11GB, but I run the training code and obtain the following errors:

/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py:1890: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py:1961: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
"See the documentation of nn.Upsample for details.".format(mode))
/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py:1006: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
Traceback (most recent call last):
File "train.py", line 152, in
main()
File "train.py", line 81, in main
train(net, optimizer)
File "train.py", line 112, in train
loss4_h2l = bce_logit(predict4_h2l, labels)
File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/loss.py", line 573, in forward
reduction=self.reduction)
File "/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py", line 1651, in binary_cross_entropy_with_logits
loss = input - input * target + max_val + ((-max_val).exp() + (-input - max_val).exp()).log()
RuntimeError: CUDA error: out of memory

I want to know how to solve is problem. As the same time, I try to change the batch size 8 to a smaller batch size 4, but it does not work, and outputs the following errors:

/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py:1890: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py:1961: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
"See the documentation of nn.Upsample for details.".format(mode))
/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py:1006: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
Traceback (most recent call last):
File "train.py", line 153, in
main()
File "train.py", line 82, in main
train(net, optimizer)
File "train.py", line 121, in train
loss.backward()
File "/usr/local/lib/python2.7/dist-packages/torch/tensor.py", line 93, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/usr/local/lib/python2.7/dist-packages/torch/autograd/init.py", line 90, in backward
allow_unreachable=True) # allow_unreachable flag
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation

So can you help me solve this issue? Very thank you.