lm-sys / lm-sys/FastChat

ValueError: FSDP requires PyTorch >= 2.1.0

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Description

Hi,
my env as belows :
docker image : docker run --gpus all -it --net=host --ipc=host --ulimit memlock=-1 -v /home/ubuntu/test:/home/finetune -v /ssd/gyou:/models --name=vicuna nvcr.io/nvidia/pytorch:23.07-py3

run command :
root@g0300:/home/finetune/FastChat# cat ./scripts/train_vicuna_13b.sh
torchrun --nproc_per_node=8 --master_port=20001 fastchat/train/train_mem.py
--model_name_or_path /models/vicuna-13b
--data_path data/dummy_conversation.json
--bf16 True
--output_dir output_vicuna_13b
--num_train_epochs 3
--per_device_train_batch_size 4
--per_device_eval_batch_size 32
--gradient_accumulation_steps 4
--evaluation_strategy "steps"
--eval_steps 1500
--save_strategy "steps"
--save_steps 1500
--save_total_limit 8
--learning_rate 2e-5
--weight_decay 0.
--warmup_ratio 0.04
--lr_scheduler_type "cosine"
--logging_steps 1
--fsdp "full_shard auto_wrap offload"
--fsdp_transformer_layer_cls_to_wrap 'LlamaDecoderLayer'
--tf32 True
--model_max_length 2048
--gradient_checkpointing True
--lazy_preprocess True

root@g0300:/home/finetune/FastChat# pip list |grep torch
pytorch-quantization 2.1.2
torch 2.1.0a0+b5021ba
torch-tensorrt 1.5.0.dev0
torchdata 0.7.0a0
torchtext 0.16.0a0
torchvision 0.16.0a0

while I will encounter ValueError: FSDP requires PyTorch >= 2.1.0

anyone can help me have a check ? thanks very much

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with scripts/train_vicuna_13b.sh and fastchat/train/train_mem.py, then reproduce the command in the reported NVIDIA PyTorch container and inspect how the FSDP version requirement is evaluated. Compare that check with the reported torch 2.1.0a0+b5021ba version; done means the issue explains or corrects the rejection for this environment.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
distributed-systems, machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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