#!/usr/bin/env bash # Global Omni with Qwen audio, traditional audio, and high-rate person evidence. # Usage: bash run_easycom_highrate_person_av.sh \ # [all|global|qwen_audio|traditional_audio|highrate|test] [seed ...] set -euo pipefail cd "$(dirname "$0")" FEATURE_ROOT=${FEATURE_ROOT:-/data1/yfzx/wangx/Datasets/easycom/omni_features/open_stream_2fps_8s_last4_stack} TARGET_ROOT=${TARGET_ROOT:-/data1/yfzx/wangx/Datasets/easycom/easycom_target_frame} QWEN_LOCAL_ROOT=${QWEN_LOCAL_ROOT:-/data1/yfzx/wangx/Datasets/easycom/omni_features/local_qwen_1s_encoded_tf4576} HIGHRATE_LOCAL_ROOT=${HIGHRATE_LOCAL_ROOT:-/data1/yfzx/wangx/Datasets/easycom/omni_features/local_muvap_asd_25hz_v2} CHECKPOINT_ROOT=${CHECKPOINT_ROOT:-checkpoints/easycom_highrate_person_av} RESULT_ROOT=${RESULT_ROOT:-results/easycom_highrate_person_av_screen} TEST_RESULT_ROOT=${TEST_RESULT_ROOT:-results/easycom_highrate_person_av_test} EPOCHS=${EPOCHS:-4} WARMUP_EPOCHS=${WARMUP_EPOCHS:-1.6} LOCAL_PROJECTION_DIM=${LOCAL_PROJECTION_DIM:-256} PERSON_ATTENTION_DIM=${PERSON_ATTENTION_DIM:-256} PERSON_ATTENTION_HEADS=${PERSON_ATTENTION_HEADS:-4} SUMMARIZE=${SUMMARIZE:-1} read -r -a TRAIN_SESSION_ARGS <<< "${TRAIN_SESSIONS:-4 5 6 7 8 9 10 11 12}" read -r -a DEV_SESSION_ARGS <<< "${DEV_SESSIONS:-12}" read -r -a SCREEN_SESSION_ARGS <<< "${SCREEN_SESSIONS:-12}" export OMP_NUM_THREADS=${OMP_NUM_THREADS:-4} export MKL_NUM_THREADS=${MKL_NUM_THREADS:-4} export OPENBLAS_NUM_THREADS=${OPENBLAS_NUM_THREADS:-4} variant=${1:-all} if (( $# )); then shift; fi if (( $# )); then seeds=("$@"); else seeds=(0 1 2); fi case "$variant" in all) variants=(global qwen_audio traditional_audio highrate) ;; global|qwen_audio|traditional_audio|highrate) variants=("$variant") ;; test) variants=(global qwen_audio traditional_audio highrate) ;; *) echo "Expected all, global, qwen_audio, traditional_audio, highrate, or test" >&2; exit 2 ;; esac mkdir -p "$CHECKPOINT_ROOT" "$RESULT_ROOT" run_inference() { local checkpoint=$1 local_root=$2 output=$3 shift 3 if [[ -e "$output/metrics.json" ]]; then echo "Refusing to overwrite $output/metrics.json" >&2 return 1 fi local local_args=() if [[ -n "$local_root" ]]; then local_args=(--local-feature-root "$local_root") fi python infer_turn_head.py \ --feature-root "$FEATURE_ROOT" \ --target-root "$TARGET_ROOT" \ "${local_args[@]}" \ --checkpoint "$checkpoint" \ --output-dir "$output" \ --sessions "$@" \ --expected-mode open-stream-replay \ --device cuda:0 } if [[ "$variant" == test ]]; then mkdir -p "$TEST_RESULT_ROOT" for selected in "${variants[@]}"; do for seed in "${seeds[@]}"; do checkpoint="$CHECKPOINT_ROOT/${selected}_seed${seed}.pth" [[ -s "$checkpoint" ]] || { echo "Missing checkpoint: $checkpoint" >&2; exit 1; } if [[ "$selected" == global ]]; then local_root= elif [[ "$selected" == qwen_audio ]]; then local_root=$QWEN_LOCAL_ROOT else local_root=$HIGHRATE_LOCAL_ROOT fi run_inference "$checkpoint" "$local_root" \ "$TEST_RESULT_ROOT/${selected}_seed${seed}" 3 2 1 done done summary_root=$TEST_RESULT_ROOT else for selected in "${variants[@]}"; do for seed in "${seeds[@]}"; do checkpoint="$CHECKPOINT_ROOT/${selected}_seed${seed}.pth" result="$RESULT_ROOT/${selected}_seed${seed}" initialization_args=() local_args=() if [[ -e "$checkpoint" || -e "$result/metrics.json" ]]; then echo "Refusing to overwrite $checkpoint or $result" >&2 exit 1 fi if [[ "$selected" == global ]]; then local_root= modalities=av fusion=pooled elif [[ "$selected" == qwen_audio ]]; then local_root=$QWEN_LOCAL_ROOT modalities=audio fusion=pooled elif [[ "$selected" == traditional_audio ]]; then local_root=$HIGHRATE_LOCAL_ROOT modalities=audio fusion=pooled else local_root=$HIGHRATE_LOCAL_ROOT modalities=av fusion=highrate-person-av-attention audio_checkpoint="$CHECKPOINT_ROOT/traditional_audio_seed${seed}.pth" [[ -s "$audio_checkpoint" ]] || { echo "Missing matched audio checkpoint: $audio_checkpoint" >&2 echo "Run: bash run_easycom_highrate_person_av.sh traditional_audio $seed" >&2 exit 1 } initialization_args=(--initialize-pooled-checkpoint "$audio_checkpoint") fi if [[ -n "$local_root" ]]; then local_args=( --local-feature-root "$local_root" --local-modalities "$modalities" ) fi echo "$(date): ${selected}, seed=${seed}" python train_turn_head.py \ --feature-root "$FEATURE_ROOT" \ --target-root "$TARGET_ROOT" \ "${local_args[@]}" \ --local-fusion "$fusion" \ --local-projection-dim "$LOCAL_PROJECTION_DIM" \ --person-attention-dim "$PERSON_ATTENTION_DIM" \ --person-attention-heads "$PERSON_ATTENTION_HEADS" \ "${initialization_args[@]}" \ --output "$checkpoint" \ --sessions "${TRAIN_SESSION_ARGS[@]}" \ --dev-sessions "${DEV_SESSION_ARGS[@]}" \ --epochs "$EPOCHS" \ --batch-size 512 \ --learning-rate 7e-5 \ --weight-decay 5e-5 \ --warmup-epochs "$WARMUP_EPOCHS" \ --warmup-factor 0.3 \ --dropout 0.2 \ --loss lstr-mce \ --transition-objective none \ --layer-fusion concat-mlp \ --expected-mode open-stream-replay \ --seed "$seed" \ --device cuda:0 run_inference "$checkpoint" "$local_root" "$result" "${SCREEN_SESSION_ARGS[@]}" done done summary_root=$RESULT_ROOT fi if [[ "$SUMMARIZE" == 1 ]]; then python summarize_local_baselines.py \ --root "$summary_root" \ --dataset easycom \ --protocol causal_valid_only \ --paired-deltas fi