mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
82 lines
2.8 KiB
82 lines
2.8 KiB
#!/bin/bash
|
|
set_n_least_used_CUDA_VISIBLE_DEVICES() {
|
|
local n=${1:-"9999"}
|
|
echo "GPU Memory Usage:"
|
|
local FIRST_N_GPU_IDS=$(nvidia-smi --query-gpu=memory.used --format=csv |
|
|
tail -n +2 |
|
|
nl -v 0 |
|
|
tee /dev/tty |
|
|
sort -g -k 2 |
|
|
awk '{print $1}' |
|
|
head -n $n)
|
|
export CUDA_VISIBLE_DEVICES=$(echo $FIRST_N_GPU_IDS | sed 's/ /,/g')
|
|
echo "Now CUDA_VISIBLE_DEVICES is set to:"
|
|
echo "CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"
|
|
}
|
|
set_n_least_used_CUDA_VISIBLE_DEVICES 8
|
|
|
|
PROJECT_NAME="PPO"
|
|
|
|
PARENT_SAVE_DIR="" # Path to a folder to save checkpoints
|
|
PARENT_CONFIG_FILE="" # Path to a folder to save training config logs
|
|
PRETRAINED_MODEL_PATH="" # local pretrained model path (from RLHF step 1: SFT)
|
|
PRETRAINED_TOKENIZER_PATH="" # huggingface or local tokenizer path
|
|
REWARD_MODEL_PATH="" # local reward model path (from RLHF step 2: Train Reward Model)
|
|
CONVERSATION_TEMPLATE_CONFIG_PATH="" # path to the conversation config file
|
|
|
|
declare -a prompt_dataset=(
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00000
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00001
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00002
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00003
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00004
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00005
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00006
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00007
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00008
|
|
YOUR/PROMPT/DATA/DIR/arrow/part-00009
|
|
)
|
|
|
|
declare -a ptx_dataset=(
|
|
YOUR/SFT/DATA/DIR/arrow/part-00000
|
|
YOUR/SFT/DATA/DIR/arrow/part-00001
|
|
YOUR/SFT/DATA/DIR/arrow/part-00002
|
|
YOUR/SFT/DATA/DIR/arrow/part-00003
|
|
YOUR/SFT/DATA/DIR/arrow/part-00004
|
|
YOUR/SFT/DATA/DIR/arrow/part-00005
|
|
YOUR/SFT/DATA/DIR/arrow/part-00006
|
|
YOUR/SFT/DATA/DIR/arrow/part-00007
|
|
YOUR/SFT/DATA/DIR/arrow/part-00008
|
|
YOUR/SFT/DATA/DIR/arrow/part-00009
|
|
)
|
|
|
|
TIMESTAMP=$(date +%Y-%m-%d-%H-%M-%S)
|
|
FULL_PROJECT_NAME="${PROJECT_NAME}-${TIMESTAMP}"
|
|
SAVE_DIR="${PARENT_SAVE_DIR}${FULL_PROJECT_NAME}"
|
|
CONFIG_FILE="${PARENT_CONFIG_FILE}${FULL_PROJECT_NAME}.json"
|
|
|
|
colossalai run --nproc_per_node 8 --hostfile hostfile --master_port 31312 train_ppo.py \
|
|
--pretrain $PRETRAINED_MODEL_PATH \
|
|
--rm_pretrain $PRETRAINED_MODEL_PATH \
|
|
--tokenizer_dir $PRETRAINED_TOKENIZER_PATH \
|
|
--rm_checkpoint_path $REWARD_MODEL_PATH \
|
|
--prompt_dataset ${prompt_dataset[@]} \
|
|
--conversation_template_config $CONVERSATION_TEMPLATE_CONFIG_PATH \
|
|
--ptx_coef 0.0 \
|
|
--plugin "zero2" \
|
|
--save_interval 500 \
|
|
--save_path $SAVE_DIR \
|
|
--num_episodes 2000 \
|
|
--num_collect_steps 2 \
|
|
--num_update_steps 1 \
|
|
--experience_batch_size 4 \
|
|
--train_batch_size 4 \
|
|
--accumulation_steps 2 \
|
|
--lr 9e-6 \
|
|
--mixed_precision "bf16" \
|
|
--grad_clip 0.1\
|
|
--weight_decay 0.01 \
|
|
--warmup_steps 40 \
|
|
--grad_checkpoint \
|
|
--use_wandb
|