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In the example T5 training code, the main function creates a copy of the model and dataset regardless of the worker rank before passing it to FSDP. Does this mean that there are n copies of the model and dataset when running the script with torchrun and n processes?
The text was updated successfully, but these errors were encountered:
My code is set up in a similar way as the T5 example code and the memory consumption per gpu is the same regardless of the number of torchrun processes I use, so it does seem like I am creating n copies of the model. How can I avoid this?
In the example T5 training code, the main function creates a copy of the model and dataset regardless of the worker rank before passing it to FSDP. Does this mean that there are n copies of the model and dataset when running the script with torchrun and n processes?
The text was updated successfully, but these errors were encountered: