#!/bin/bash
# Flux LoRA Training with DeepSpeed ZeRO-3 on 2x H100 NVL
# Step 1: Pre-compute embeddings (one-time)
# Step 2: Train with both GPUs in parallel
#
# Usage: bash scripts/training/run_train_flux_deepspeed.sh

set -e

PROJECT_DIR="/home/adminuser/chungcat"
EMBEDDING_DIR="/data0/datasets/processed/flux_train/embeddings"
SHARD_DIR="/data0/datasets/processed/flux_train/shards"

export PYTHONPATH="$PROJECT_DIR:$PYTHONPATH"
export HF_HOME="/home/adminuser/.cache/huggingface"
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True

# Step 1: Pre-compute embeddings if not done
if [ ! -d "$EMBEDDING_DIR" ] || [ $(ls "$EMBEDDING_DIR"/shard-*.pt 2>/dev/null | wc -l) -eq 0 ]; then
    echo "=== Pre-computing embeddings ==="
    python3 "$PROJECT_DIR/scripts/training/precompute_embeddings.py" \
        --data-dir "$SHARD_DIR" \
        --output-dir "$EMBEDDING_DIR" \
        --batch-size 8 \
        --device cuda:0
    echo "=== Embeddings ready ==="
fi

# Step 2: Launch DeepSpeed training on 2 GPUs
echo "=== Starting DeepSpeed ZeRO-3 Training ==="
accelerate launch \
    --config_file "$PROJECT_DIR/configs/accelerate_config.yaml" \
    "$PROJECT_DIR/scripts/training/train_flux_deepspeed.py" \
    --embedding-dir "$EMBEDDING_DIR" \
    --output-dir "/data0/checkpoints/flux_lora_ds" \
    --batch-size 1 \
    --gradient-accumulation 8 \
    --learning-rate 1e-4 \
    --lr-warmup-steps 500 \
    --max-train-steps 100000 \
    --save-steps 5000 \
    --lora-rank 128 \
    --lora-alpha 128