RuntimeError: CUDA out of memory，continuous training？

[watertianyi]

I have trained 3000 pairs of data, and want to add another 2000 pairs to continue training, using the following command:
python train.py --name comics --dataroot ./datasets/comics3Kto5K --loadSize 512 --label_nc 0 --no_instance --netG local --load_pretrain checkpoints0310/comics/

But the error is as follows:
#RuntimeError: CUDA out of memory. Tried to allocate 98.00 MiB (GPU 0; 11.76 GiB total capacity; 8.86 GiB already allocated; 113.56 MiB free; 8.91 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
What is going on?

[takuyaliu]

Restart

[watertianyi]

@takuyaliu If training is interrupted, can't I continue training from the breakpoint?

[takuyaliu]

Of course you can train it from the latest breakpoint, you can find it in base options and train options.

[watertianyi]

@takuyaliu
How should set the parameters, thank you for your reply!

[takuyaliu]

@takuyaliu How should set the parameters, thank you for your reply!

You can find it in 'options/train_options.py'

for training

    self.parser.add_argument('--continue_train', action='store_true', help='continue training: load the latest model')
    self.parser.add_argument('--which_epoch', type=str, default='latest', help='which epoch to load? set to latest to use latest cached model')

try to add '--continue_train --which_epoch latest' after your training command.