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#!/bin/bash
# Debug script for MDPO training in VSCode
# This script sets up the environment and runs the training with debugging support
# Environment Variables
export RANK=1
export MASTER_PORT=29571
# Training Arguments
export LOCAL_BATCH_SIZE=2
export GRADIENT_ACCUMULATION_STEPS=4
# Path Arguments
export TRANSFORMERS_OFFLINE=1
export WANDB_PROJECT=vtimellm
export MODEL_VERSION=vicuna-v1-5-7b
export OUTPUT_DIR=./outputs/
export STAGE4=./outputs/vtimellm-vicuna-v1-5-7b-activitynet-stage4
export RUN_NAME=vtimellm-$MODEL_VERSION-activitynet-stage5
# Debug environment variables
export PYTHONPATH="${PYTHONPATH}:$(pwd)"
export CUDA_VISIBLE_DEVICES=1
export TORCH_USE_CUDA_DSA=1
# Enable debug logging
export TRANSFORMERS_VERBOSITY=info
export TOKENIZERS_PARALLELISM=false
# Create output directory if it doesn't exist
mkdir -p $OUTPUT_DIR/$RUN_NAME
echo "=== Debug Environment Setup ==="
echo "RANK: $RANK"
echo "MASTER_PORT: $MASTER_PORT"
echo "CUDA_VISIBLE_DEVICES: $CUDA_VISIBLE_DEVICES"
echo "PYTHONPATH: $PYTHONPATH"
echo "OUTPUT_DIR: $OUTPUT_DIR/$RUN_NAME"
echo "================================"
# Check if required files exist
echo "=== Checking Required Files ==="
required_files=(
"./checkpoints/vicuna-7b-v1.5"
"./data/activitynet/mdpo-train.json"
"./data/activitynet/videos/train"
"./data/activitynet/clipvitl14-vtimellm.pth"
"./checkpoints/vtimellm-vicuna-v1-5-7b-stage1/mm_projector.bin"
"./checkpoints/vtimellm-vicuna-v1-5-7b-stage2"
"./checkpoints/vtimellm-vicuna-v1-5-7b-stage3"
"./checkpoints/vtimellm-vicuna-v1-5-7b-activitynet-stage4"
"./scripts/zero2.json"
)
for file in "${required_files[@]}"; do
if [ -e "$file" ]; then
echo "✓ Found: $file"
else
echo "✗ Missing: $file"
fi
done
echo "================================"
# Check GPU availability
echo "=== GPU Information ==="
nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader,nounits
echo "================================"
# Run the training with debugging support
echo "=== Starting Debug Training ==="
echo "Command: deepspeed --include localhost:$RANK --master_port $MASTER_PORT vtimellm/train/train_dpo_mem.py [args...]"
echo "================================"
# Execute the training command
deepspeed --include localhost:$RANK --master_port $MASTER_PORT vtimellm/train/train_dpo_mem.py \
--deepspeed ./scripts/zero2.json \
--lora_enable True --lora_r 8 --lora_alpha 128 \
--training_stage 3 --finetuning True \
--model_name_or_path ./checkpoints/vicuna-7b-v1.5 \
--version v1 \
--data_path ./data/activitynet/mdpo-train.json \
--data_folder ./data/activitynet/videos/train \
--feat_folder ./data/activitynet/clipvitl14-vtimellm.pth \
--pretrain_mm_mlp_adapter ./checkpoints/vtimellm-vicuna-v1-5-7b-stage1/mm_projector.bin \
--stage2_path ./checkpoints/vtimellm-vicuna-v1-5-7b-stage2 \
--stage3_path ./checkpoints/vtimellm-vicuna-v1-5-7b-stage3 \
--stage4_path checkpoints/vtimellm-vicuna-v1-5-7b-activitynet-stage4 \
--output_dir $OUTPUT_DIR/$RUN_NAME \
--bf16 True \
--max_steps 100 \
--per_device_train_batch_size $LOCAL_BATCH_SIZE \
--gradient_accumulation_steps $GRADIENT_ACCUMULATION_STEPS \
--evaluation_strategy "no" \
--save_strategy "no" \
--save_steps 50000 \
--save_total_limit 10 \
--learning_rate 1e-6 \
--freeze_mm_mlp_adapter True \
--weight_decay 0. --warmup_ratio 0.1 --lr_scheduler_type "cosine" \
--logging_steps 1 \
--tf32 True \
--model_max_length 2048 \
--gradient_checkpointing True \
--dataloader_num_workers 4 \
--lazy_preprocess True \
--report_to "none" \
--run_name $RUN_NAME \
--gamma 0.0 --beta 0.5 --dpo_alpha 1.0 --train4dpo
echo "=== Training Completed ==="
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