mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-12 19:04:03 +08:00
Ethan Weberandevonneng
7e9a56fac4
* starting docs for pipelines * working on an example * clearing output * starting to implement config changes and add documentation * wip: removed cicular imports; porting basic config into python; todo: get python setups workin * circular imports again * wip: pausing at dataloader sort of working * break for today * running vanilla * wip need to get all the config docs working * laptop about to die * instant ngp working * added all configs for all methods; not tested yet: [mipnerf360, nerfw, semantic_nerf] * unpacking later * done with pylinting * mostly done. just need to do docs and one test * added import order to docs * fixing near/far plane and other config things * making loggers also instantiable via configs * docs * lint * making --help work with dcargs * moving configs back into flat * convert list to tuples; fixed post init function with mutable params * lint * made run_eval and benchmarking scripts compatible with new config/dcargs * lint * added option to load configs from presaved config Co-authored-by: evonneng <evonne_ng@berkeley.edu>
74 lines
2.4 KiB
Bash
Executable File
74 lines
2.4 KiB
Bash
Executable File
helpFunction_launch_eval()
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{
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echo "Usage: $0 -c config_name -g gpu_list"
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echo -e "\t-c name of method to benchmark (e.g. graph_mipnerf, graph_instant_ngp)"
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echo -o "\t-o base directory for where all the benchmarks are stored (e.g. outputs/)"
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echo -e "\t-m month of the benchmark of format xx (e.g. 08)"
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echo -e "\t-d date of the benchmark of format xx (e.g. 01)"
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echo -e "\t-y year of the benchmark of format xxxx (e.g. 2022)"
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echo -e "\t-s second timestamp of the benchmark of format xxxxxx (e.g. 003603)"
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echo -e "\t-g list of space-separated gpu numbers to launch train on (e.g. 0 2 4 5)"
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exit 1 # Exit program after printing help
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}
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while getopts "c:o:m:d:y:s:g" opt; do
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case "$opt" in
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c ) config_name="$OPTARG" ;;
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o ) output_dir="$OPTARG" ;;
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m ) month="$OPTARG" ;;
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d ) date="$OPTARG" ;;
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y ) year="$OPTARG" ;;
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s ) seconds="$OPTARG" ;;
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g ) gpu_list="$OPTARG" ;;
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? ) helpFunction_launch_eval ;;
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esac
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done
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if [ -z "$config_name" ]; then
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echo "Missing method name"
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helpFunction_launch_train
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fi
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shift $((OPTIND-1))
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# Deal with gpu's. If passed in, use those.
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GPU_IDX=("$@")
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if [ -z "$GPU_IDX" ]; then
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echo "no gpus set... finding available gpus"
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# Find available devices
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num_device=$(nvidia-smi --query-gpu=name --format=csv,noheader | wc -l)
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START=0
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END=${num_device}-1
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GPU_IDX=()
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for (( id=$START; id<$END; id++ )); do
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free_mem=$(nvidia-smi --query-gpu=memory.free --format=csv -i $id | grep -Eo [0-9]+)
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if [[ $free_mem -gt 10000 ]]; then
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GPU_IDX+=( $id )
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fi
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done
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fi
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echo available gpus... ${GPU_IDX[@]}
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DATASETS=("mic" "ficus" "chair" "hotdog" "materials" "drums" "ship" "lego")
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idx=0
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len=${#GPU_IDX[@]}
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((len=len-1))
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for dataset in ${DATASETS[@]}; do
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export CUDA_VISIBLE_DEVICES=${GPU_IDX[$idx]}
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base_config_name=${config_name/"graph_"/""}
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checkpoint_dir="${output_dir}/blender_${dataset}_${month}-${date}-${year}/${base_config_name}/${year}-${month}-${date}_${seconds}/nerfactory_models/"
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python scripts/run_eval.py ${config_name} \
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--eval.checkpoint-dir=${checkpoint_dir} \
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--eval.output-filename=${output_dir}/${base_config_name}/blender_${dataset}_${month}-${date}-${year}_${seconds}.json &
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echo "Launched ${checkpoint_dir} on gpu ${GPU_IDX[$idx]}"
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# update gpu
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if [ $idx == $len ]; then
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idx=0
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else
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((idx=idx+1))
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fi
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done |