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OptimalScale / LMFlow

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
https://optimalscale.github.io/LMFlow/
Apache License 2.0
8.22k stars 821 forks source link

Training was successful on a single card 4090GPU, but an error was reported on a 3*4090GPU. why #841

Open orderer0001 opened 4 months ago

orderer0001 commented 4 months ago

(lmflow_train) root@duxact:/data/projects/lmflow/LMFlow# ./scripts/run_finetune_with_lisa.sh \ --model_name_or_path /data/guihunmodel8.8B \ --dataset_path /data/projects/lmflow/case_report_data \ --output_model_path /data/projects/lmflow/guihun_fintune_model \ --lisa_activated_layers 1 \ --lisa_interval_steps 20 [2024-05-22 14:32:20,602] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) /root/anaconda3/envs/lmflow_train/lib/python3.9/site-packages/transformers/deepspeed.py:23: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations warnings.warn( Traceback (most recent call last): File "/data/projects/lmflow/LMFlow/examples/finetune.py", line 61, in main() File "/data/projects/lmflow/LMFlow/examples/finetune.py", line 44, in main model_args, data_args, pipeline_args = parser.parse_args_into_dataclasses() File "/root/anaconda3/envs/lmflow_train/lib/python3.9/site-packages/transformers/hf_argparser.py", line 339, in parse_args_into_dataclasses obj = dtype(**inputs) File "", line 135, in init File "/root/anaconda3/envs/lmflow_train/lib/python3.9/site-packages/transformers/training_args.py", line 1641, in __post_init and (self.device.type == "cpu" and not is_torch_greater_or_equal_than_2_3) File "/root/anaconda3/envs/lmflow_train/lib/python3.9/site-packages/transformers/training_args.py", line 2149, in device return self._setup_devices File "/root/anaconda3/envs/lmflow_train/lib/python3.9/site-packages/transformers/utils/generic.py", line 59, in get cached = self.fget(obj) File "/root/anaconda3/envs/lmflow_train/lib/python3.9/site-packages/transformers/training_args.py", line 2081, in _setup_devices self.distributed_state = PartialState( File "/root/anaconda3/envs/lmflow_train/lib/python3.9/site-packages/accelerate/state.py", line 293, in init__ raise NotImplementedError( NotImplementedError: Using RTX 4000 series doesn't support faster communication broadband via P2P or IB. Please set NCCL_P2P_DISABLE="1" and NCCL_IB_DISABLE="1" or useaccelerate launch` which will do this automatically.

wheresmyhair commented 4 months ago

Thanks for your interest in LMFlow! Currently we are working on the full multi-GPU support for LISA. Please stay tuned for our latest update, thanks for your understanding 🙏