wehub-resource-sync
170 lines
4.5 KiB
Bash
170 lines
4.5 KiB
Bash
#!/bin/bash
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output_dir=output
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# ============ start of custom code block ==========
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config_file=''
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model_paths_file=''
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if [ -n "$1" ]; then
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config_file=$1
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fi
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if [ -n "$2" ]; then
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model_paths_file=$2
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fi
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# ============ end of custom code block ===========
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default_step=20
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default_bs=50 # 1
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default_sample_nums=30000
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default_sampling_algo="flow_dpm-solver"
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json_file="data/test/PG-eval-data/MJHQ-30K/meta_data.json"
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default_add_label=''
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default_dataset='MJHQ-30K'
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default_img_size=512 # 1024
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default_fid_suffix_label='30K_bs50_Flow_DPM20' # suffix of the line chart on wandb
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default_log_fid=false
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default_log_clip_score=false
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# 👇No need to change the code below
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job_name=$(basename $(dirname $(dirname "$model_paths_file")))
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for arg in "$@"
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do
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case $arg in
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--step=*)
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step="${arg#*=}"
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shift
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;;
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--bs=*)
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bs="${arg#*=}"
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shift
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;;
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--sample_nums=*)
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sample_nums="${arg#*=}"
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shift
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;;
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--sampling_algo=*)
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sampling_algo="${arg#*=}"
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shift
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;;
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--dataset=*)
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dataset="${arg#*=}"
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shift
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;;
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--img_size=*)
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img_size="${arg#*=}"
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shift
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;;
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--cfg_scale=*)
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cfg_scale="${arg#*=}"
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shift
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;;
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--fid_suffix_label=*)
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fid_suffix_label="${arg#*=}"
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shift
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;;
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--add_label=*)
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add_label="${arg#*=}"
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shift
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;;
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--log_fid=*)
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log_fid="${arg#*=}"
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shift
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;;
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--log_clip_score=*)
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log_clip_score="${arg#*=}"
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shift
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;;
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--auto_ckpt=*)
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auto_ckpt="${arg#*=}"
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shift
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;;
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--auto_ckpt_interval=*)
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auto_ckpt_interval="${arg#*=}"
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shift
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;;
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--inference_script=*)
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inference_script="${arg#*=}"
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shift
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;;
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--inference=*)
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inference="${arg#*=}"
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shift
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;;
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--fid=*)
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fid="${arg#*=}"
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shift
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;;
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--clipscore=*)
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clipscore="${arg#*=}"
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shift
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;;
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--tracker_pattern=*)
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tracker_pattern="${arg#*=}"
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shift
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;;
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--tracker_project_name=*)
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tracker_project_name="${arg#*=}"
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shift
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;;
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--ablation_key=*)
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ablation_key="${arg#*=}"
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shift
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;;
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--ablation_selections=*)
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ablation_selections="${arg#*=}"
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shift
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;;
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--cleanup=*)
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cleanup="${arg#*=}"
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shift
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;;
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*)
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;;
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esac
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done
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inference_script=${inference_script:-"scripts/inference.py"}
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inference=${inference:-true} # if run model inference
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fid=${fid:-true} # if compute fid
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clipscore=${clipscore:-true} # if compute clip-score
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step=${step:-$default_step}
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bs=${bs:-$default_bs}
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dataset=${dataset:-$default_dataset}
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cfg_scale=${cfg_scale:-4.5}
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sample_nums=${sample_nums:-$default_sample_nums}
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sampling_algo=${sampling_algo:-$default_sampling_algo}
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img_size=${img_size:-$default_img_size}
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fid_suffix_label=${fid_suffix_label:-$default_fid_suffix_label}
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add_label=${add_label:-$default_add_label}
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ablation_key=${ablation_key:-''}
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ablation_selections=${ablation_selections:-''}
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tracker_pattern=${tracker_pattern:-"epoch_step"}
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tracker_project_name=${tracker_project_name:-"sana-baseline"}
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log_fid=${log_fid:-$default_log_fid}
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log_clip_score=${log_clip_score:-$default_log_clip_score}
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auto_ckpt=${auto_ckpt:-false} # if collect ckpt path automatically, use with the following one $auto_ckpt_interval
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auto_ckpt_interval=${auto_ckpt_interval:-0} # 0:last step in one epoch; 1000: every 1000 steps
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cleanup=${cleanup:-false}
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read -r -d '' cmd <<EOF
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bash scripts/infer_metric_run_inference_metric.sh $config_file $model_paths_file \
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--inference_script=$inference_script --inference=$inference --fid=$fid --clipscore=$clipscore \
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--step=$step --bs=$bs --sample_nums=$sample_nums --json_file=$json_file \
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--exist_time_prefix=$exist_time_prefix --img_size=$img_size --cfg_scale=$cfg_scale \
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--fid_suffix_label=$fid_suffix_label --add_label=$add_label --dataset=$dataset \
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--log_fid=$log_fid --log_clip_score=$log_clip_score \
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--output_dir=$output_dir --auto_ckpt=$auto_ckpt --sampling_algo=$sampling_algo \
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--auto_ckpt_interval=$auto_ckpt_interval --tracker_pattern=$tracker_pattern \
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--ablation_key=$ablation_key --ablation_selections="$ablation_selections" --cleanup=$cleanup \
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--tracker_project_name=$tracker_project_name
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EOF
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echo $cmd '\n'
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bash -c "${cmd}"
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