Austin

Results 7 comments of Austin

Maybe you can try as follows: 1.Adjust the strict parameter: Modify the code so that it sets allow_partial_load to not strict when calling torch.distributed.checkpoint.load, ensuring that partial loading is allowed...

By default, PyTorch creates the model on the CPU, unless you explicitly move it to a different device (e.g. via .to(device)). As a result, even with trainer.init_module(), the model will...

Here are some of my opinions: Causes: num_checkpoints Parameter not passed: num_checkpoints is the number of checkpoints used to activate, but is not properly passed to the relevant function during...

Maybe you can change your IDE to light mode to make the background white.

Avoid exit(1): In a Jupyter environment, exit() can cause problems. exit is possible in standard Python scripts, but should not be called in Jupyter notebooks. You can use sys.exit() instead:...