docs: replace torch.distributed.run by torchrun (#27528)
* docs: replace torch.distributed.run by torchrun `transformers` now officially support pytorch >= 1.10. The entrypoint `torchrun`` is present from 1.10 onwards. Signed-off-by: Peter Pan <Peter.Pan@daocloud.io> * Update src/transformers/trainer.py with @ArthurZucker's suggestion Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> --------- Signed-off-by: Peter Pan <Peter.Pan@daocloud.io> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
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@@ -134,7 +134,7 @@ Ecco il codice benchmark completo e gli output:
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```bash
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# DDP w/ NVLink
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rm -r /tmp/test-clm; CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch \
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rm -r /tmp/test-clm; CUDA_VISIBLE_DEVICES=0,1 torchrun \
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--nproc_per_node 2 examples/pytorch/language-modeling/run_clm.py --model_name_or_path gpt2 \
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--dataset_name wikitext --dataset_config_name wikitext-2-raw-v1 --do_train \
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--output_dir /tmp/test-clm --per_device_train_batch_size 4 --max_steps 200
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@@ -143,7 +143,7 @@ rm -r /tmp/test-clm; CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch
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# DDP w/o NVLink
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rm -r /tmp/test-clm; CUDA_VISIBLE_DEVICES=0,1 NCCL_P2P_DISABLE=1 python -m torch.distributed.launch \
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rm -r /tmp/test-clm; CUDA_VISIBLE_DEVICES=0,1 NCCL_P2P_DISABLE=1 torchrun \
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--nproc_per_node 2 examples/pytorch/language-modeling/run_clm.py --model_name_or_path gpt2 \
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--dataset_name wikitext --dataset_config_name wikitext-2-raw-v1 --do_train
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--output_dir /tmp/test-clm --per_device_train_batch_size 4 --max_steps 200
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