#!/bin/bash

helpFunction_launch_train()
{
   echo "Usage: $0 -m <method_name> [-v <vis>] [-s] [<gpu_list>]"
   echo -e "\t-m name of config to benchmark (e.g. mipnerf, instant_ngp)"
   echo -e "\t-v <vis>: Visualization method. <vis> can be wandb or tensorboard. Default is wandb."
   echo -e "\t-s: Launch a single training job per gpu."
   echo -e "\t<gpu_list> [OPTIONAL] list of space-separated gpu numbers to launch train on (e.g. 0 2 4 5)"
   exit 1 # Exit program after printing help
}

vis="wandb"
single=false
while getopts "m:v:s" opt; do
    case "$opt" in
        m ) method_name="$OPTARG" ;;
        v ) vis="$OPTARG" ;;
        s ) single=true ;;
        ? ) helpFunction ;; 
    esac
done

if [ -z "${method_name+x}" ]; then
    echo "Missing method name"
    helpFunction_launch_train
fi
method_opts=()
if [ "$method_name" = "nerfacto" ]; then
    # https://github.com/nerfstudio-project/nerfstudio/issues/806#issuecomment-1284327844
    method_opts=(--pipeline.model.near-plane 2. --pipeline.model.far-plane 6. --pipeline.datamanager.camera-optimizer.mode off --pipeline.model.use-average-appearance-embedding False)
fi

shift $((OPTIND-1))

# Deal with gpu's. If passed in, use those.
GPU_IDX=("$@")
if [ -z "${GPU_IDX[0]+x}" ]; then
    echo "no gpus set... finding available gpus"
    # Find available devices
    num_device=$(nvidia-smi --query-gpu=name --format=csv,noheader | wc -l)
    START=0
    END=${num_device}-1
    GPU_IDX=()

    for (( id=START; id<=END; id++ )); do
        free_mem=$(nvidia-smi --query-gpu=memory.free --format=csv -i $id | grep -Eo '[0-9]+')
        if [[ $free_mem -gt 10000 ]]; then
            GPU_IDX+=( "$id" )
        fi
    done
fi
echo "available gpus... ${GPU_IDX[*]}"

DATASETS=("mic" "ficus" "chair" "hotdog" "materials" "drums" "ship" "lego")
date
tag=$(date +'%Y-%m-%d')
idx=0
len=${#GPU_IDX[@]}
GPU_PID=()
timestamp=$(date "+%Y-%m-%d_%H%M%S")
# kill all the background jobs if terminated:
trap "trap - SIGTERM && kill -- -$$" SIGINT SIGTERM EXIT

for dataset in "${DATASETS[@]}"; do
    if "$single" && [ -n "${GPU_PID[$idx]+x}" ]; then
        echo "Waiting for GPU ${GPU_IDX[$idx]}"
        wait "${GPU_PID[$idx]}"
        echo "GPU ${GPU_IDX[$idx]} is available"
    fi
    export CUDA_VISIBLE_DEVICES="${GPU_IDX[$idx]}"
    ns-train "${method_name}" "${method_opts[@]}" \
             --data="data/blender/${dataset}" \
             --experiment-name="blender_${dataset}_${tag}" \
             --trainer.relative-model-dir=nerfstudio_models/ \
             --trainer.steps-per-save=1000 \
             --trainer.max-num-iterations=16500 \
             --logging.local-writer.enable=False  \
             --logging.enable-profiler=False \
             --vis "${vis}" \
             --timestamp "$timestamp" \
             blender-data & GPU_PID[$idx]=$!
    echo "Launched ${method_name} ${dataset} on gpu ${GPU_IDX[$idx]}, ${tag}"
    
    # update gpu
    ((idx=(idx+1)%len))
done
wait
echo "Done."
echo "Launch eval with:"
s=""
$single && s="-s"
echo "$(dirname "$0")/launch_eval_blender.sh -m $method_name -o outputs/ -t $timestamp $s"