How to run on CPU?

BramVanroy · April 1, 2022, 9:32am

You’ll have to force the accelerator to run on CPU.

huggingface/transformers/blob/9de70f213eb234522095cc9af7b2fac53afc2d87/examples/pytorch/token-classification/run_ner_no_trainer.py#L230

      
        
                if args.push_to_hub:
                    assert args.output_dir is not None, "Need an `output_dir` to create a repo when `--push_to_hub` is passed."
            
            
    return args
            
            

            
def main():
                args = parse_args()
            
            
    # Initialize the accelerator. We will let the accelerator handle device placement for us in this example.
                accelerator = Accelerator()
                # Make one log on every process with the configuration for debugging.
                logging.basicConfig(
                    format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
                    datefmt="%m/%d/%Y %H:%M:%S",
                    level=logging.INFO,
                )
                logger.info(accelerator.state)
            
            
    # Setup logging, we only want one process per machine to log things on the screen.
                # accelerator.is_local_main_process is only True for one process per machine.

accelerator = Accelerator(cpu=True)

should do the trick.

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How to run on CPU?

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