I’m working on a kaggle notebook and I have trained a model (which represents OCR (PyTorch)) and saved the checkpoints, now I am trying to load the saved checkpoints to complete the previous training…

When I run this cell to continue training, the following error message appears and the execution is stopped:

start_epoch = 0
# load checkpoint
start_epoch = load_checkpoint(model, optimizer, '/kaggle/input/for-checkpoints/cp_23.pth')


# Training Loop

for epoch in range(start_epoch, 24):
    print(f'Epoch [{epoch+1}/{24}]:')

    Train(model, train_dataloader, ctc_loss, optimizer, device)

    scheduler.step()
    save_checkpoint(model, optimizer, epoch, '/kaggle/working/')

    Test(model, test_dataloader, ctc_loss, device)

This is the message that appears after execution:

/tmp/ipykernel_36/1025039100.py:13: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_data = torch.load(checkpoint_path)

I want, even if this message appears, to complete the training and bring the checkpoints anyway.