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#!/bin/bash
# Set default values for distributed training parameters
# 禁用WandB
export WANDB_DISABLED=true
# ===== GPU配置参数 =====
# export CUDA_VISIBLE_DEVICES=0,1,2,3 # 使用4张GPU
export CUDA_VISIBLE_DEVICES=0 # GPU编号
export GPUS_PER_NODE=1 # 每个节点GPU数量
export n_node=1 # 单节点
export CURRENT_RANK=0 # 当前节点rank
export MASTER_ADDR="localhost" # 主节点地址
export MASTER_PORT=48057 # 主节点端口
llama3_model_path="/home/user/NaVILA/checkpoints/navila-llama3-8b-8f"
GEOMETRY_ENCODER_TYPE="pi3"
GEOMETRY_ENCODER_PATH="/home/user/NaVILA/checkpoints/Pi3"
# GEOMETRY_ENCODER_TYPE="vggt"
# GEOMETRY_ENCODER_PATH="/home/user/NaVILA/checkpoints/VGGT-1B"
OUTPUT="/home/user/NaVILA/sft_8frames"
# 检查是否有检查点可以resume
if [ -d "$OUTPUT" ] && [ "$(ls -A $OUTPUT | grep -E 'tmp-checkpoint-|checkpoint-')" ]; then
echo "Found existing checkpoints, will resume from the latest one"
# 找到最新的检查点
LATEST_CHECKPOINT=$(ls -t $OUTPUT | grep -E 'tmp-checkpoint-|checkpoint-' | head -1)
RESUME_PATH="$OUTPUT/$LATEST_CHECKPOINT"
echo "Resuming from: $RESUME_PATH"
# 不删除输出目录，让训练自动resume
else
echo "No existing checkpoints found, starting fresh training"
# rm -rf /home/user/NaVILA/output*
RESUME_PATH="$llama3_model_path"
fi
torchrun --nnodes=$n_node --nproc_per_node=$GPUS_PER_NODE --master_port=$MASTER_PORT \
--master_addr $MASTER_ADDR --node_rank=$CURRENT_RANK \
llava/train/train_mem.py \
--longvila_sampler True \
--deepspeed ./scripts/zero3.json \
--model_name_or_path $RESUME_PATH \
--version llama_3 \
--seed 3407 \
--data_mixture r2r+rxr \
--vision_tower google/siglip-so400m-patch14-384 \
--mm_vision_select_feature cls_patch \
--mm_projector mlp_downsample \
--num_video_frames 16 \
--tune_vision_tower False \
--tune_mm_projector True \
--tune_language_model True \
--mm_vision_select_layer -2 \
--mm_use_im_start_end False \
--mm_use_im_patch_token False \
--image_aspect_ratio resize \
--bf16 True \
--output_dir $OUTPUT \
--num_train_epochs 5 \
--per_device_train_batch_size 10 \
--gradient_accumulation_steps 2 \
--do_eval False \
--save_strategy "steps" \
--save_steps 2000 \
--fps 0.0 \
--save_total_limit 10 \
--learning_rate 1e-4 \
--mm_projector_lr 1e-5 \
--geometry_merger_lr 1e-4 \
--feature_fusion_lr 1e-4 \
--llm_lr 1e-6 \
--weight_decay 0. \
--warmup_ratio 0.03 \
--lr_scheduler_type "cosine" \
--logging_steps 1 \
--tf32 True \
--model_max_length 4096 \
--gradient_checkpointing True \
--dataloader_num_workers 16 \
--lazy_preprocess True \
--report_to tensorboard \
--logging_dir $OUTPUT/runs \
--use_geometry_encoder True \
--geometry_encoder_type $GEOMETRY_ENCODER_TYPE \
--geometry_encoder_path $GEOMETRY_ENCODER_PATH \
--feature_fusion_method "residual" \
--voxel_size 0.2 \ |