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83 lines
2.9 KiB
83 lines
2.9 KiB
#!/bin/bash
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set_n_least_used_CUDA_VISIBLE_DEVICES() {
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local n=${1:-"9999"}
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echo "GPU Memory Usage:"
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local FIRST_N_GPU_IDS=$(nvidia-smi --query-gpu=memory.used --format=csv |
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tail -n +2 |
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nl -v 0 |
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tee /dev/tty |
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sort -g -k 2 |
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awk '{print $1}' |
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head -n $n)
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export CUDA_VISIBLE_DEVICES=$(echo $FIRST_N_GPU_IDS | sed 's/ /,/g')
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echo "Now CUDA_VISIBLE_DEVICES is set to:"
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echo "CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"
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}
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set_n_least_used_CUDA_VISIBLE_DEVICES 8
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PROJECT_NAME="ppo"
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PARENT_SAVE_DIR="" # Path to a folder to save checkpoints
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PARENT_TENSORBOARD_DIR="" # Path to a folder to save logs
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PARENT_CONFIG_FILE="" # Path to a folder to save training config logs
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PRETRAINED_MODEL_PATH="" # local pretrained model path (from RLHF step 1: SFT)
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PRETRAINED_TOKENIZER_PATH="" # huggingface or local tokenizer path
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REWARD_MODEL_PATH="" # local reward model path (from RLHF step 2: Train Reward Model)
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CONVERSATION_TEMPLATE_CONFIG_PATH="" # path to the conversation config file
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declare -a prompt_dataset=(
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YOUR/PROMPT/DATA/DIR/arrow/part-00000
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YOUR/PROMPT/DATA/DIR/arrow/part-00001
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YOUR/PROMPT/DATA/DIR/arrow/part-00002
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YOUR/PROMPT/DATA/DIR/arrow/part-00003
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YOUR/PROMPT/DATA/DIR/arrow/part-00004
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YOUR/PROMPT/DATA/DIR/arrow/part-00005
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YOUR/PROMPT/DATA/DIR/arrow/part-00006
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YOUR/PROMPT/DATA/DIR/arrow/part-00007
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YOUR/PROMPT/DATA/DIR/arrow/part-00008
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YOUR/PROMPT/DATA/DIR/arrow/part-00009
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)
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declare -a ptx_dataset=(
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YOUR/SFT/DATA/DIR/arrow/part-00000
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YOUR/SFT/DATA/DIR/arrow/part-00001
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YOUR/SFT/DATA/DIR/arrow/part-00002
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YOUR/SFT/DATA/DIR/arrow/part-00003
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YOUR/SFT/DATA/DIR/arrow/part-00004
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YOUR/SFT/DATA/DIR/arrow/part-00005
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YOUR/SFT/DATA/DIR/arrow/part-00006
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YOUR/SFT/DATA/DIR/arrow/part-00007
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YOUR/SFT/DATA/DIR/arrow/part-00008
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YOUR/SFT/DATA/DIR/arrow/part-00009
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)
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TIMESTAMP=$(date +%Y-%m-%d-%H-%M-%S)
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FULL_PROJECT_NAME="${PROJECT_NAME}-${TIMESTAMP}"
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SAVE_DIR="${PARENT_SAVE_DIR}${FULL_PROJECT_NAME}"
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CONFIG_FILE="${PARENT_CONFIG_FILE}-${FULL_PROJECT_NAME}.json"
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colossalai run --nproc_per_node 8 --hostfile hostfile --master_port 31312 train_ppo.py \
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--pretrain $PRETRAINED_MODEL_PATH \
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--rm_pretrain $PRETRAINED_MODEL_PATH \
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--tokenizer_dir $PRETRAINED_TOKENIZER_PATH \
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--rm_checkpoint_path $REWARD_MODEL_PATH \
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--prompt_dataset ${prompt_dataset[@]} \
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--conversation_template_config $CONVERSATION_TEMPLATE_CONFIG_PATH \
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--ptx_coef 0.0 \
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--plugin "zero2" \
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--save_interval 500 \
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--save_path $SAVE_DIR \
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--num_episodes 2000 \
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--num_collect_steps 2 \
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--num_update_steps 1 \
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--experience_batch_size 4 \
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--train_batch_size 4 \
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--accumulation_steps 2 \
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--lr 9e-6 \
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--mixed_precision "bf16" \
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--grad_clip 0.1\
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--weight_decay 0.01 \
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--warmup_steps 40 \
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--grad_checkpoint \
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--use_wandb
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