I am trying to use the BigGAN model, but I found the below error during test when I generated images using the pretrained weights. How Can I solve the problem? (Not related to the memory)
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RuntimeError                              Traceback (most recent call last)
/tmp/ipykernel_34/2818109655.py in <module>
     12                # real_img = imgs.to(device)
     13                # bs = imgs.size(0)
---> 14                 fake_imgs = pretrained_G(imgs.cuda())
     15 
     16 

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

/tmp/ipykernel_34/2782497050.py in forward(self, z)
     66         # Feed through generator blocks
     67         for idx, g_block in enumerate(self.g_blocks):
---> 68             h = g_block(h)
     69            # h = g_block[1](h)
     70 

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

/tmp/ipykernel_34/2262133493.py in forward(self, x)
     31 
     32         # Compute dot product attention with query (theta) and key (phi) matrices
---> 33         beta = F.softmax(torch.bmm(theta.transpose(1, 2), phi), dim=-1)
     34 
     35         # Compute scaled dot product attention with value (g) and attention (beta) matrices

RuntimeError: CUDA out of memory. Tried to allocate 6.00 GiB (GPU 0; 15.90 GiB total capacity; 6.89 GiB already allocated; 2.16 GiB free; 12.68 GiB reserved in total by PyTorch)