mirror of https://github.com/hpcaitech/ColossalAI
63 lines
2.0 KiB
Bash
Executable File
63 lines
2.0 KiB
Bash
Executable File
#!/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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# export CUDA_VISIBLE_DEVICES=6
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PROJECT_NAME="dpo"
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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="" # huggingface or local model path
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PRETRAINED_TOKENIZER_PATH="" # huggingface or local tokenizer path
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declare -a dataset=(
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YOUR/DATA/DIR/arrow/part-00000
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YOUR/DATA/DIR/arrow/part-00001
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YOUR/DATA/DIR/arrow/part-00002
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YOUR/DATA/DIR/arrow/part-00003
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YOUR/DATA/DIR/arrow/part-00004
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YOUR/DATA/DIR/arrow/part-00005
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YOUR/DATA/DIR/arrow/part-00006
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YOUR/DATA/DIR/arrow/part-00007
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YOUR/DATA/DIR/arrow/part-00008
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YOUR/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_dpo.py \
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--pretrain $PRETRAINED_MODEL_PATH \
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--checkpoint_path $PRETRAINED_MODEL_PATH \
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--tokenizer_dir $PRETRAINED_TOKENIZER_PATH \
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--dataset ${dataset[@]} \
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--plugin "zero2" \
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--save_interval 1000 \
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--save_dir $SAVE_DIR \
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--config_file $CONFIG_FILE \
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--max_epochs 1 \
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--accumulation_steps 4 \
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--batch_size 2 \
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--lr 1e-6 \
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--mixed_precision "bf16" \
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--grad_clip 1.0 \
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--weight_decay 0.01 \
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--warmup_steps 100 \
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--grad_checkpoint \
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--use_wandb
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