Image-Text-to-Text
Transformers
Safetensors
qwen3_5
vllm
video
multimodal
reinforcement-learning
temporal-grounding
object-tracking
video-segmentation
visual-question-answering
spatial-reasoning
qwen3.5
conversational
Instructions to use OraRL/Video-ORA-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OraRL/Video-ORA-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OraRL/Video-ORA-9B") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("OraRL/Video-ORA-9B") model = AutoModelForMultimodalLM.from_pretrained("OraRL/Video-ORA-9B", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OraRL/Video-ORA-9B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OraRL/Video-ORA-9B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OraRL/Video-ORA-9B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/OraRL/Video-ORA-9B
- SGLang
How to use OraRL/Video-ORA-9B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "OraRL/Video-ORA-9B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OraRL/Video-ORA-9B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "OraRL/Video-ORA-9B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OraRL/Video-ORA-9B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use OraRL/Video-ORA-9B with Docker Model Runner:
docker model run hf.co/OraRL/Video-ORA-9B
File size: 46,210 Bytes
53c10a4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 | #!/bin/bash
# Thin shell entry for evaluation.
#
# Supported TASKS: videomme,videommev2,videommmu,mmvu,mvbench,videoholmes,longvideobench,lvbench,mlvu,vsi,mmsi,mindcube,revsi,spatial_grounding,tracking,stvg,temporal_grounding,segmentation,all
# Common env overrides:
# MODEL_PATH=/path/to/model_or_verl_actor
# TASKS=videomme,videommev2,vsi
# GPUS=0,1,2,3,4,5,6,7
# TP_SIZE=1
# Prefer explicit CLI args for new runs, which avoids stale env variables:
# bash eval/task/eval.sh --model /path/to/model --tasks videomme,videommev2,mvbench --gpus 0,1,2,3,4,5,6,7 --force-merge
#
# MODEL must be provided explicitly with --model.
# # —— Video QA / MC ——
# bash eval/task/eval.sh --model $MODEL --tasks mvbench --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks mmvu --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks videomme --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks videoholmes --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks longvideobench --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks mlvu --gpus $GPUS --force-merge
# # —— Spatial intelligence (MC) ——
# bash eval/task/eval.sh --model $MODEL --tasks vsi --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks mmsi --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks mindcube --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks revsi --gpus $GPUS --force-merge
# # —— Grounding / tracking / stvg / temporal ——
# bash eval/task/eval.sh --model $MODEL --tasks spatial_grounding --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks tracking --gpus $GPUS --force-merge
# bash eval/task/eval.sh --model $MODEL --tasks stvg --gpus $GPUS --force-merge
# charades(默认)
# TIMELENS_DATASETS=charades-timelens TIMELENS_FPS=4 bash eval/task/eval.sh --model $MODEL --tasks temporal_grounding --gpus $GPUS --force-merge
# TIMELENS_DATASETS=activitynet-timelens TIMELENS_FPS=2 bash eval/task/eval.sh --model $MODEL --tasks temporal_grounding --gpus $GPUS --force-merge
# TIMELENS_DATASETS=qvhighlights-timelens TIMELENS_FPS=2 bash eval/task/eval.sh --model $MODEL --tasks temporal_grounding --gpus $GPUS --force-merge
# # —— Segmentation(需要 SAM2 + OraRL 评测环境)——
# EVAL_CONDA_ENV=orarl SEGMENTATION_RUN_SAM2=true \
# bash eval/task/eval.sh --model $MODEL --tasks segmentation --gpus $GPUS --force-merge
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
PROJECT_DIR="$(cd "${SCRIPT_DIR}/../.." && pwd)"
DEFAULT_GPUS="0,1,2,3,4,5,6,7"
usage() {
cat <<'EOF'
Usage:
bash eval/task/eval.sh [options]
Options:
--model PATH Model or checkpoint path.
--tasks LIST Comma-separated task list, e.g. videomme,videommev2,mvbench,mlvu.
--gpus LIST Comma-separated GPU ids, e.g. 0,1,2,3,4,5,6,7.
--tp-size N Tensor parallel size.
--shard-mode MODE Sharding mode passed to vLLM task runner.
--video-cache-size N Video cache size.
--videomme-max-new-tokens N
Max new tokens for VideoMME generation.
--force-merge Force merging FSDP actor checkpoints.
--skip-merge Reuse existing merged HF model for actor checkpoints.
--merged-model PATH Explicit merged HF output/input path for actor checkpoints.
--base-model PATH Base model path used when merging actor checkpoints.
--env NAME Conda env to activate. Default: keep current env.
--segmentation-run-sam2
Enable SAM2 post-processing for segmentation.
--help Show this help.
Core launch settings intentionally ignore inherited environment variables to
avoid stale MODEL_PATH/TASKS/GPUS/etc. Use explicit CLI options instead.
EOF
}
# Avoid stale shell environment contaminating evaluation identity. Task-specific
# tuning envs below are still supported, but core launch identity is CLI/defaults.
unset MODEL_PATH TASKS GPUS TP_SIZE SHARD_MODE VIDEO_CACHE_SIZE
unset FORCE_MERGE SKIP_MERGE MERGED_MODEL_PATH BASE_MODEL_PATH EVAL_CONDA_ENV
while (($# > 0)); do
case "$1" in
--model|--model-path)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
MODEL_PATH="$2"
shift 2
;;
--tasks)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
TASKS="$2"
shift 2
;;
--gpus)
if [[ $# -ge 2 && "$2" != --* ]]; then
GPUS="$2"
shift 2
else
GPUS="$DEFAULT_GPUS"
shift
fi
;;
--tp-size)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
TP_SIZE="$2"
shift 2
;;
--shard-mode)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
SHARD_MODE="$2"
shift 2
;;
--video-cache-size)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
VIDEO_CACHE_SIZE="$2"
shift 2
;;
--videomme-max-new-tokens)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
VIDEOMME_MAX_NEW_TOKENS="$2"
shift 2
;;
--force-merge)
FORCE_MERGE=1
shift
;;
--skip-merge)
SKIP_MERGE=1
shift
;;
--merged-model|--merged-model-path)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
MERGED_MODEL_PATH="$2"
shift 2
;;
--base-model|--base-model-path)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
BASE_MODEL_PATH="$2"
shift 2
;;
--env|--conda-env)
[[ $# -ge 2 ]] || { echo "ERROR: $1 requires a value" >&2; exit 1; }
EVAL_CONDA_ENV="$2"
shift 2
;;
--segmentation-run-sam2)
SEGMENTATION_RUN_SAM2=true
shift
;;
--help|-h)
usage
exit 0
;;
--)
shift
break
;;
*)
echo "ERROR: unknown option '$1'" >&2
usage >&2
exit 1
;;
esac
done
# Require an explicit model so stale machine-local defaults cannot contaminate
# benchmark results.
if [[ -z "${MODEL_PATH:-}" ]]; then
echo "ERROR: --model PATH is required." >&2
usage >&2
exit 2
fi
MODEL_PATH="$(printf '%s' "$MODEL_PATH" | xargs)"
# Common launch defaults.
: "${TASKS:=all}"
: "${GPUS:=$DEFAULT_GPUS}"
: "${TP_SIZE:=1}"
: "${SHARD_MODE:=contiguous}"
: "${VIDEO_CACHE_SIZE:=2}"
: "${PREFETCH_BATCHES:=1}"
: "${FORCE_MERGE:=0}"
: "${SKIP_MERGE:=0}"
: "${MERGE_LOG_DIR:=${PROJECT_DIR}/logs/qwen3.5/eval/merge}"
if [[ ! "$GPUS" =~ ^[0-9]+(,[0-9]+)*$ ]]; then
echo "ERROR: --gpus must be a comma-separated list of GPU ids, got '${GPUS}'" >&2
exit 1
fi
# VideoMME defaults.
: "${VIDEOMME_VIDEO_BASE:=${PROJECT_DIR}/data/eval/videomme}"
: "${VIDEOMME_VIDEO_DIR:=${VIDEOMME_VIDEO_BASE}/videos}"
: "${VIDEOMME_VIDEO_MIN_PIXELS:=4096}"
: "${VIDEOMME_VIDEO_MAX_PIXELS:=262144}"
: "${VIDEOMME_VIDEO_TOTAL_PIXELS:=0}"
: "${VIDEOMME_MAX_FRAMES:=384}"
: "${VIDEOMME_FPS:=2}"
: "${VIDEOMME_SETTING:=all-qwen3_vl-sub0-f${VIDEOMME_MAX_FRAMES}-fps${VIDEOMME_FPS}-min${VIDEOMME_VIDEO_MIN_PIXELS}-max${VIDEOMME_VIDEO_MAX_PIXELS}-total${VIDEOMME_VIDEO_TOTAL_PIXELS}-videomme_preprocessed_384f_262k_total0}"
: "${VIDEOMME_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/videomme_preprocessed_384f_262k_total0.jsonl}"
: "${VIDEOMME_PREPROCESSED_VIDEO_DIR:=${VIDEOMME_VIDEO_BASE}/preprocessed_videos_384f_262k_total0}"
: "${VIDEOMME_BATCH_SIZE:=1}"
: "${VIDEOMME_MAX_MODEL_LEN:=65536}"
: "${VIDEOMME_MAX_NEW_TOKENS:=128}"
: "${VIDEOMME_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${VIDEOMME_GPU_MEMORY_UTILIZATION:=0.90}"
: "${VIDEOMME_MAX_SAMPLES:=0}"
# VideoMME-V2 defaults. Uses the same local schema and evaluator as VideoMME.
: "${VIDEOMMEV2_VIDEO_BASE:=${PROJECT_DIR}/data/eval/videommev2}"
: "${VIDEOMMEV2_VIDEO_DIR:=${VIDEOMMEV2_VIDEO_BASE}/videos}"
: "${VIDEOMMEV2_VIDEO_MIN_PIXELS:=4096}"
: "${VIDEOMMEV2_VIDEO_MAX_PIXELS:=262144}"
: "${VIDEOMMEV2_VIDEO_TOTAL_PIXELS:=0}"
: "${VIDEOMMEV2_MAX_FRAMES:=384}"
: "${VIDEOMMEV2_FPS:=2}"
: "${VIDEOMMEV2_SETTING:=all-qwen3_vl-sub0-f${VIDEOMMEV2_MAX_FRAMES}-fps${VIDEOMMEV2_FPS}-min${VIDEOMMEV2_VIDEO_MIN_PIXELS}-max${VIDEOMMEV2_VIDEO_MAX_PIXELS}-total${VIDEOMMEV2_VIDEO_TOTAL_PIXELS}-videommev2_preprocessed_384f_262k_total0}"
: "${VIDEOMMEV2_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/videommev2_preprocessed_384f_262k_total0.jsonl}"
: "${VIDEOMMEV2_PREPROCESSED_VIDEO_DIR:=${VIDEOMMEV2_VIDEO_BASE}/preprocessed_videos_384f_262k_total0}"
: "${VIDEOMMEV2_BATCH_SIZE:=1}"
: "${VIDEOMMEV2_MAX_MODEL_LEN:=65536}"
: "${VIDEOMMEV2_MAX_NEW_TOKENS:=128}"
: "${VIDEOMMEV2_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${VIDEOMMEV2_GPU_MEMORY_UTILIZATION:=0.90}"
: "${VIDEOMMEV2_PROMPT_MODE:=default}"
: "${VIDEOMMEV2_ANSWER_FILTER:=}"
: "${VIDEOMMEV2_MAX_SAMPLES:=0}"
# VideoMMMU defaults.
: "${VIDEOMMMU_SETTING:=videommmu-f128-fps2-min4096-max262144-total0-with-image}"
: "${VIDEOMMMU_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/videommmu_with_image.json}"
: "${VIDEOMMMU_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/videommmu}"
: "${VIDEOMMMU_BATCH_SIZE:=4}"
: "${VIDEOMMMU_MAX_MODEL_LEN:=65536}"
: "${VIDEOMMMU_MAX_NEW_TOKENS:=128}"
: "${VIDEOMMMU_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${VIDEOMMMU_GPU_MEMORY_UTILIZATION:=0.90}"
: "${VIDEOMMMU_VIDEO_MIN_PIXELS:=4096}"
: "${VIDEOMMMU_VIDEO_MAX_PIXELS:=262144}"
: "${VIDEOMMMU_VIDEO_TOTAL_PIXELS:=0}"
: "${VIDEOMMMU_MAX_FRAMES:=128}"
: "${VIDEOMMMU_FPS:=2}"
# OneThinker-style Adaptation uses subject videos + PNGs extracted from
# Adaptation/test-00000-of-00001.parquet. Run once before eval:
# python3 eval/data/extract_videommmu_images.py
# prompt_mode=onethink reproduces OneThinker's CoT prompt; pair it with a large
# VIDEOMMMU_MAX_NEW_TOKENS (OneThinker uses 8192).
: "${VIDEOMMMU_PROMPT_MODE:=default}"
# Separate Adaptation image resolution cap (OneThinker uses 1024*32*32=1048576).
: "${VIDEOMMMU_IMAGE_MAX_PIXELS:=1048576}"
# Qwen3.5 native benchmarking: thinking on + recommended sampling + long output.
# To reproduce the official VideoMMMU number, run with:
# VIDEOMMMU_PROMPT_MODE=qwen VIDEOMMMU_ENABLE_THINKING=true
# VIDEOMMMU_MAX_NEW_TOKENS=32768 VIDEOMMMU_MAX_MODEL_LEN=131072
# VIDEOMMMU_TEMPERATURE=1.0 VIDEOMMMU_TOP_P=0.95 VIDEOMMMU_TOP_K=20 VIDEOMMMU_PRESENCE_PENALTY=1.5
: "${VIDEOMMMU_ENABLE_THINKING:=false}"
: "${VIDEOMMMU_TEMPERATURE:=0.0}"
: "${VIDEOMMMU_TOP_P:=1.0}"
: "${VIDEOMMMU_TOP_K:=-1}"
: "${VIDEOMMMU_PRESENCE_PENALTY:=0.0}"
: "${VIDEOMMMU_MIN_P:=0.0}"
# MMVU defaults (multiple-choice subset, raw video).
# Build the MC JSONL once: python scripts/build_mmvu_mc.py
: "${MMVU_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/mmvu_mc.jsonl}"
: "${MMVU_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/mmvu}"
: "${MMVU_BATCH_SIZE:=1}"
: "${MMVU_MAX_MODEL_LEN:=65536}"
: "${MMVU_MAX_NEW_TOKENS:=128}"
: "${MMVU_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${MMVU_GPU_MEMORY_UTILIZATION:=0.90}"
: "${MMVU_VIDEO_MIN_PIXELS:=4096}"
: "${MMVU_VIDEO_MAX_PIXELS:=262144}"
: "${MMVU_VIDEO_TOTAL_PIXELS:=0}"
: "${MMVU_MAX_FRAMES:=384}"
: "${MMVU_FPS:=2}"
: "${MMVU_PROMPT_MODE:=default}"
# Qwen3.5 native: MMVU_PROMPT_MODE=qwen MMVU_ENABLE_THINKING=true with large
# MMVU_MAX_NEW_TOKENS / sampling, mirroring VideoMMMU.
: "${MMVU_ENABLE_THINKING:=false}"
: "${MMVU_TEMPERATURE:=0.0}"
: "${MMVU_TOP_P:=1.0}"
: "${MMVU_TOP_K:=-1}"
: "${MMVU_PRESENCE_PENALTY:=0.0}"
: "${MMVU_MIN_P:=0.0}"
: "${MMVU_MAX_SAMPLES:=0}"
: "${MMVU_SETTING:=mmvu-mc-f${MMVU_MAX_FRAMES}-fps${MMVU_FPS}-min${MMVU_VIDEO_MIN_PIXELS}-max${MMVU_VIDEO_MAX_PIXELS}-total${MMVU_VIDEO_TOTAL_PIXELS}-${MMVU_PROMPT_MODE}}"
# MVBench defaults (multi-task short-video multiple-choice).
: "${MVBENCH_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/mvbench.json}"
: "${MVBENCH_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/mvbench}"
: "${MVBENCH_BATCH_SIZE:=1}"
: "${MVBENCH_MAX_MODEL_LEN:=65536}"
: "${MVBENCH_MAX_NEW_TOKENS:=128}"
: "${MVBENCH_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${MVBENCH_GPU_MEMORY_UTILIZATION:=0.90}"
: "${MVBENCH_VIDEO_MIN_PIXELS:=4096}"
: "${MVBENCH_VIDEO_MAX_PIXELS:=262144}"
: "${MVBENCH_VIDEO_TOTAL_PIXELS:=0}"
: "${MVBENCH_MAX_FRAMES:=384}"
: "${MVBENCH_FPS:=2}"
: "${MVBENCH_PROMPT_MODE:=default}"
: "${MVBENCH_ENABLE_THINKING:=false}"
: "${MVBENCH_TEMPERATURE:=0.0}"
: "${MVBENCH_TOP_P:=1.0}"
: "${MVBENCH_TOP_K:=-1}"
: "${MVBENCH_PRESENCE_PENALTY:=0.0}"
: "${MVBENCH_MIN_P:=0.0}"
: "${MVBENCH_MAX_SAMPLES:=0}"
: "${MVBENCH_SETTING:=mvbench-f${MVBENCH_MAX_FRAMES}-fps${MVBENCH_FPS}-min${MVBENCH_VIDEO_MIN_PIXELS}-max${MVBENCH_VIDEO_MAX_PIXELS}-total${MVBENCH_VIDEO_TOTAL_PIXELS}-${MVBENCH_PROMPT_MODE}}"
# Video-Holmes defaults (all multiple-choice, raw cropped videos).
# Download: huggingface-cli download TencentARC/Video-Holmes --repo-type dataset
# Build: python scripts/build_videoholmes.py
: "${VIDEOHOLMES_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/videoholmes.jsonl}"
: "${VIDEOHOLMES_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/videoholmes}"
: "${VIDEOHOLMES_BATCH_SIZE:=1}"
: "${VIDEOHOLMES_MAX_MODEL_LEN:=65536}"
: "${VIDEOHOLMES_MAX_NEW_TOKENS:=128}"
: "${VIDEOHOLMES_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${VIDEOHOLMES_GPU_MEMORY_UTILIZATION:=0.90}"
: "${VIDEOHOLMES_VIDEO_MIN_PIXELS:=4096}"
: "${VIDEOHOLMES_VIDEO_MAX_PIXELS:=262144}"
: "${VIDEOHOLMES_VIDEO_TOTAL_PIXELS:=0}"
: "${VIDEOHOLMES_MAX_FRAMES:=384}"
: "${VIDEOHOLMES_FPS:=2}"
: "${VIDEOHOLMES_PROMPT_MODE:=default}"
# Official benchmark prompt is reasoning-style:
# VIDEOHOLMES_PROMPT_MODE=holmes VIDEOHOLMES_ENABLE_THINKING=true VIDEOHOLMES_MAX_NEW_TOKENS=1024
: "${VIDEOHOLMES_ENABLE_THINKING:=false}"
: "${VIDEOHOLMES_TEMPERATURE:=0.0}"
: "${VIDEOHOLMES_TOP_P:=1.0}"
: "${VIDEOHOLMES_TOP_K:=-1}"
: "${VIDEOHOLMES_PRESENCE_PENALTY:=0.0}"
: "${VIDEOHOLMES_MIN_P:=0.0}"
: "${VIDEOHOLMES_MAX_SAMPLES:=0}"
: "${VIDEOHOLMES_SETTING:=videoholmes-f${VIDEOHOLMES_MAX_FRAMES}-fps${VIDEOHOLMES_FPS}-min${VIDEOHOLMES_VIDEO_MIN_PIXELS}-max${VIDEOHOLMES_VIDEO_MAX_PIXELS}-total${VIDEOHOLMES_VIDEO_TOTAL_PIXELS}-${VIDEOHOLMES_PROMPT_MODE}}"
# LongVideoBench defaults. Main videos/subtitles repo is gated; after getting
# access, download/extract to LONGVIDEOBENCH_VIDEO_ROOT with videos/ + subtitles/.
# Build validation JSONL: python scripts/build_longvideobench.py
: "${LONGVIDEOBENCH_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/longvideobench_val.jsonl}"
: "${LONGVIDEOBENCH_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/longvideobench}"
: "${LONGVIDEOBENCH_SUBTITLE_ROOT:=$LONGVIDEOBENCH_VIDEO_ROOT}"
: "${LONGVIDEOBENCH_USE_SUBTITLES:=true}"
: "${LONGVIDEOBENCH_BATCH_SIZE:=1}"
: "${LONGVIDEOBENCH_MAX_MODEL_LEN:=65536}"
: "${LONGVIDEOBENCH_MAX_NEW_TOKENS:=128}"
: "${LONGVIDEOBENCH_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${LONGVIDEOBENCH_GPU_MEMORY_UTILIZATION:=0.90}"
: "${LONGVIDEOBENCH_VIDEO_MIN_PIXELS:=4096}"
: "${LONGVIDEOBENCH_VIDEO_MAX_PIXELS:=262144}"
: "${LONGVIDEOBENCH_VIDEO_TOTAL_PIXELS:=0}"
: "${LONGVIDEOBENCH_MAX_FRAMES:=384}"
: "${LONGVIDEOBENCH_FPS:=2}"
: "${LONGVIDEOBENCH_PROMPT_MODE:=default}"
: "${LONGVIDEOBENCH_ENABLE_THINKING:=false}"
: "${LONGVIDEOBENCH_TEMPERATURE:=0.0}"
: "${LONGVIDEOBENCH_TOP_P:=1.0}"
: "${LONGVIDEOBENCH_TOP_K:=-1}"
: "${LONGVIDEOBENCH_PRESENCE_PENALTY:=0.0}"
: "${LONGVIDEOBENCH_MIN_P:=0.0}"
: "${LONGVIDEOBENCH_MAX_SAMPLES:=0}"
: "${LONGVIDEOBENCH_SETTING:=longvideobench-val-f${LONGVIDEOBENCH_MAX_FRAMES}-fps${LONGVIDEOBENCH_FPS}-min${LONGVIDEOBENCH_VIDEO_MIN_PIXELS}-max${LONGVIDEOBENCH_VIDEO_MAX_PIXELS}-total${LONGVIDEOBENCH_VIDEO_TOTAL_PIXELS}-${LONGVIDEOBENCH_PROMPT_MODE}}"
# LVBench defaults (long-video multiple-choice; independent from LongVideoBench).
: "${LVBENCH_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/lvbench.json}"
: "${LVBENCH_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/lvbench}"
: "${LVBENCH_BATCH_SIZE:=4}"
: "${LVBENCH_MAX_MODEL_LEN:=65536}"
: "${LVBENCH_MAX_NEW_TOKENS:=128}"
: "${LVBENCH_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${LVBENCH_GPU_MEMORY_UTILIZATION:=0.90}"
: "${LVBENCH_VIDEO_MIN_PIXELS:=4096}"
: "${LVBENCH_VIDEO_MAX_PIXELS:=262144}"
: "${LVBENCH_VIDEO_TOTAL_PIXELS:=0}"
: "${LVBENCH_MAX_FRAMES:=128}"
: "${LVBENCH_FPS:=2}"
: "${LVBENCH_PROMPT_MODE:=default}"
: "${LVBENCH_ENABLE_THINKING:=false}"
: "${LVBENCH_TEMPERATURE:=0.0}"
: "${LVBENCH_TOP_P:=1.0}"
: "${LVBENCH_TOP_K:=-1}"
: "${LVBENCH_PRESENCE_PENALTY:=0.0}"
: "${LVBENCH_MIN_P:=0.0}"
: "${LVBENCH_SETTING:=lvbench-f${LVBENCH_MAX_FRAMES}-fps${LVBENCH_FPS}-min${LVBENCH_VIDEO_MIN_PIXELS}-max${LVBENCH_VIDEO_MAX_PIXELS}-total${LVBENCH_VIDEO_TOTAL_PIXELS}-${LVBENCH_PROMPT_MODE}}"
# MLVU defaults (dev multiple-choice subset = 7 tasks, M-Avg).
# Build the MC JSONL once: python scripts/build_mlvu_mc.py
: "${MLVU_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/mlvu_mc.jsonl}"
: "${MLVU_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/mlvu}"
: "${MLVU_BATCH_SIZE:=1}"
: "${MLVU_MAX_MODEL_LEN:=65536}"
: "${MLVU_MAX_NEW_TOKENS:=128}"
: "${MLVU_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${MLVU_GPU_MEMORY_UTILIZATION:=0.90}"
: "${MLVU_VIDEO_MIN_PIXELS:=4096}"
: "${MLVU_VIDEO_MAX_PIXELS:=262144}"
: "${MLVU_VIDEO_TOTAL_PIXELS:=0}"
: "${MLVU_MAX_FRAMES:=384}"
: "${MLVU_FPS:=2}"
: "${MLVU_PROMPT_MODE:=default}"
: "${MLVU_ENABLE_THINKING:=false}"
: "${MLVU_TEMPERATURE:=0.0}"
: "${MLVU_TOP_P:=1.0}"
: "${MLVU_TOP_K:=-1}"
: "${MLVU_PRESENCE_PENALTY:=0.0}"
: "${MLVU_MIN_P:=0.0}"
: "${MLVU_MAX_SAMPLES:=0}"
: "${MLVU_SETTING:=mlvu-mc-f${MLVU_MAX_FRAMES}-fps${MLVU_FPS}-min${MLVU_VIDEO_MIN_PIXELS}-max${MLVU_VIDEO_MAX_PIXELS}-total${MLVU_VIDEO_TOTAL_PIXELS}-${MLVU_PROMPT_MODE}}"
# VSI-Bench defaults.
: "${VSI_SETTING:=video128-16M-video-f128-fps2-min65536-maxnone-total16777216-vsibench_preprocessed_128f_16M}"
: "${VSI_DATA_FILE:=${PROJECT_DIR}/eval/data/valid_data/vsibench_preprocessed_128f_16M.jsonl}"
: "${VSI_PREPROCESSED_VIDEO_DIR:=${PROJECT_DIR}/data/eval/vsi/preprocessed_videos}"
: "${VSI_BATCH_SIZE:=16}"
: "${VSI_MAX_MODEL_LEN:=32768}"
: "${VSI_MAX_NEW_TOKENS:=1024}"
: "${VSI_GPU_MEMORY_UTILIZATION:=0.90}"
: "${VSI_EXPECTED_SAMPLES:=5130}"
# MMSI-Bench defaults. Transformers is used so every image can be retained;
# set MMSI_BACKEND=vllm and MMSI_MAX_IMAGES=8 for the legacy path.
: "${MMSI_BACKEND:=transformers}"
: "${MMSI_DATA_FILE:=${PROJECT_DIR}/data/eval/mmsi/MMSI_bench.tsv}"
: "${MMSI_IMAGE_MIN_PIXELS:=4096}"
: "${MMSI_IMAGE_MAX_PIXELS:=262144}"
if [[ "${MMSI_BACKEND}" == "transformers" ]]; then
: "${MMSI_MAX_IMAGES:=0}"
else
: "${MMSI_MAX_IMAGES:=8}"
fi
: "${MMSI_IMAGE_COUNT_TAG:=$([[ "${MMSI_MAX_IMAGES}" -le 0 ]] && echo all || echo "${MMSI_MAX_IMAGES}")}"
: "${MMSI_SETTING:=${MMSI_BACKEND}-img-min${MMSI_IMAGE_MIN_PIXELS}-max${MMSI_IMAGE_MAX_PIXELS}-n${MMSI_IMAGE_COUNT_TAG}-all-MMSI_bench}"
: "${MMSI_BATCH_SIZE:=16}"
: "${MMSI_MAX_MODEL_LEN:=32768}"
: "${MMSI_MAX_NEW_TOKENS:=1024}"
: "${MMSI_MAX_NUM_BATCHED_TOKENS:=32768}"
: "${MMSI_GPU_MEMORY_UTILIZATION:=0.90}"
: "${MMSI_MAX_SAMPLES:=0}"
: "${MMSI_CATEGORY:=}"
: "${MMSI_ENABLE_THINKING:=false}"
: "${MMSI_ATTN_IMPLEMENTATION:=flash_attention_2}"
if [[ -n "${MMSI_CATEGORY}" || "${MMSI_MAX_SAMPLES}" != "0" ]]; then
: "${MMSI_EXPECTED_SAMPLES:=0}"
else
: "${MMSI_EXPECTED_SAMPLES:=1000}"
fi
# MindCube-Tiny defaults.
: "${MINDCUBE_SETTING:=img-min4096-max262144-n4-official-tiny1050}"
: "${MINDCUBE_DATA_FILE:=${PROJECT_DIR}/data/eval/mindcube_official/combined-00000-of-00001.parquet}"
: "${MINDCUBE_MAX_IMAGES:=4}"
: "${MINDCUBE_EXPECTED_SAMPLES:=1050}"
: "${MINDCUBE_HF_CACHE_DIR:=}"
: "${MINDCUBE_BATCH_SIZE:=16}"
: "${MINDCUBE_MAX_MODEL_LEN:=32768}"
: "${MINDCUBE_MAX_NEW_TOKENS:=1024}"
: "${MINDCUBE_MAX_NUM_BATCHED_TOKENS:=32768}"
: "${MINDCUBE_GPU_MEMORY_UTILIZATION:=0.90}"
# ReVSI defaults. The all-frame/native-frame profile reproduces the 58.2 result
# reported for Video-ORA-9B; ReVSI remains excluded from the three-benchmark
# spatial-intelligence average.
: "${REVSI_DATA_FILE:=${PROJECT_DIR}/data/eval/revsi/all_frame/test-00000-of-00001.parquet}"
: "${REVSI_VIDEO_ROOT:=${PROJECT_DIR}/data/eval/revsi}"
: "${REVSI_FRAME_BUDGET:=all}"
: "${REVSI_MAX_FRAMES:=128}"
: "${REVSI_EXACT_NFRAMES:=true}"
: "${REVSI_FPS:=2}"
: "${REVSI_VIDEO_MIN_PIXELS:=65536}"
: "${REVSI_VIDEO_MAX_PIXELS:=}"
: "${REVSI_VIDEO_TOTAL_PIXELS:=16777216}"
: "${REVSI_BATCH_SIZE:=16}"
: "${REVSI_MAX_MODEL_LEN:=32768}"
: "${REVSI_MAX_NEW_TOKENS:=64}"
: "${REVSI_GPU_MEMORY_UTILIZATION:=0.90}"
: "${REVSI_MAX_SAMPLES:=0}"
: "${REVSI_EXPECTED_SAMPLES:=6808}"
: "${REVSI_TASK_FILTER:=}"
: "${REVSI_ENABLE_THINKING:=false}"
: "${REVSI_SETTING:=native-all-f${REVSI_MAX_FRAMES}-exact${REVSI_EXACT_NFRAMES}-fps${REVSI_FPS}-min${REVSI_VIDEO_MIN_PIXELS}-max${REVSI_VIDEO_MAX_PIXELS:-none}-total${REVSI_VIDEO_TOTAL_PIXELS}}"
# Spatial grounding defaults, aligned to data/joint/sft_joint_all.jsonl.
: "${SPATIAL_GROUNDING_DATASETS:=refcoco-val,refcoco-testA,refcoco-testB,refcoco+-val,refcoco+-testA,refcoco+-testB,refcocog-val,refcocog-test}"
: "${SPATIAL_GROUNDING_BENCH_DIR:=${PROJECT_DIR}/eval/task/spatial_grounding}"
: "${SPATIAL_GROUNDING_IMAGE_ROOT:=${PROJECT_DIR}/data/eval/spatial_grounding/images}"
: "${SPATIAL_GROUNDING_PROCESSOR_PATH:=$MODEL_PATH}"
: "${SPATIAL_GROUNDING_PROMPT_STYLE:=qwen_native}"
: "${SPATIAL_GROUNDING_COORD_SYSTEM:=norm1000}"
: "${SPATIAL_GROUNDING_BBOX_SELECT:=first}"
: "${SPATIAL_GROUNDING_MIN_TOKENS:=64}"
: "${SPATIAL_GROUNDING_TOTAL_TOKENS:=1024}"
: "${SPATIAL_GROUNDING_BATCH_SIZE:=64}"
: "${SPATIAL_GROUNDING_MAX_MODEL_LEN:=32768}"
: "${SPATIAL_GROUNDING_MAX_NEW_TOKENS:=1024}"
: "${SPATIAL_GROUNDING_MAX_NUM_BATCHED_TOKENS:=32768}"
: "${SPATIAL_GROUNDING_GPU_MEMORY_UTILIZATION:=0.85}"
: "${SPATIAL_GROUNDING_ENABLE_THINKING:=false}"
: "${SPATIAL_GROUNDING_MAX_SAMPLES:=0}"
: "${SPATIAL_GROUNDING_SETTING:=spatial-grounding-${SPATIAL_GROUNDING_DATASETS//,/_}-${SPATIAL_GROUNDING_PROMPT_STYLE}-min${SPATIAL_GROUNDING_MIN_TOKENS}-total${SPATIAL_GROUNDING_TOTAL_TOKENS}-new${SPATIAL_GROUNDING_MAX_NEW_TOKENS}}"
# Tracking defaults, aligned to data/joint/sft_joint_all.jsonl tracking videos.
: "${TRACKING_DATASETS:=eval_got10k}"
: "${TRACKING_BENCH_DIR:=${PROJECT_DIR}/data/eval/tracking}"
: "${TRACKING_BASE_PREFIX:=$TRACKING_BENCH_DIR}"
: "${TRACKING_PROCESSOR_PATH:=$MODEL_PATH}"
: "${TRACKING_VIDEO_MIN_PIXELS:=4096}"
: "${TRACKING_VIDEO_MAX_PIXELS:=786432}"
: "${TRACKING_VIDEO_TOTAL_PIXELS:=8388608}"
: "${TRACKING_MAX_FRAMES:=32}"
: "${TRACKING_FPS:=1}"
: "${TRACKING_MAX_MODEL_LEN:=32768}"
: "${TRACKING_MAX_NEW_TOKENS:=8192}"
: "${TRACKING_MAX_NUM_BATCHED_TOKENS:=32768}"
: "${TRACKING_BATCH_SIZE:=64}"
: "${TRACKING_GPU_MEMORY_UTILIZATION:=0.95}"
: "${TRACKING_ENABLE_THINKING:=false}"
: "${TRACKING_PROMPT_MODE:=default}"
: "${TRACKING_CHUNKED_REPROMPT:=0}"
: "${TRACKING_REPROMPT_USE_GT_FIRST_BOX:=0}"
: "${TRACKING_MAX_SAMPLES:=0}"
: "${TRACKING_SETTING:=tracking-${TRACKING_DATASETS//,/_}-f${TRACKING_MAX_FRAMES}-fps${TRACKING_FPS}-min${TRACKING_VIDEO_MIN_PIXELS}-max${TRACKING_VIDEO_MAX_PIXELS}-total${TRACKING_VIDEO_TOTAL_PIXELS}-new${TRACKING_MAX_NEW_TOKENS}}"
# STVG defaults, aligned to data/joint/sft_joint_all.jsonl stvg videos.
: "${STVG_DATASETS:=eval_stvg}"
: "${STVG_BENCH_DIR:=${PROJECT_DIR}/data/eval/stvg}"
: "${STVG_BASE_PREFIX:=$STVG_BENCH_DIR}"
: "${STVG_PROCESSOR_PATH:=$MODEL_PATH}"
: "${STVG_VIDEO_MIN_PIXELS:=65536}"
: "${STVG_VIDEO_MAX_PIXELS:=393216}"
: "${STVG_VIDEO_TOTAL_PIXELS:=10485760}"
: "${STVG_MAX_FRAMES:=128}"
: "${STVG_FPS:=2}"
: "${STVG_MAX_MODEL_LEN:=65536}"
: "${STVG_MAX_NEW_TOKENS:=2048}"
: "${STVG_MAX_NUM_BATCHED_TOKENS:=65536}"
: "${STVG_BATCH_SIZE:=64}"
: "${STVG_GPU_MEMORY_UTILIZATION:=0.85}"
: "${STVG_ENABLE_THINKING:=false}"
: "${STVG_PROMPT_MODE:=train_stvg}"
: "${STVG_MAX_SAMPLES:=0}"
: "${STVG_SETTING:=stvg-${STVG_DATASETS//,/_}-f${STVG_MAX_FRAMES}-fps${STVG_FPS}-min${STVG_VIDEO_MIN_PIXELS}-max${STVG_VIDEO_MAX_PIXELS}-total${STVG_VIDEO_TOTAL_PIXELS}-new${STVG_MAX_NEW_TOKENS}-${STVG_PROMPT_MODE}}"
# Segmentation defaults.
# This task is dispatched to eval/task/segmentation/run_eval_vllm.sh,
# which performs vLLM inference plus optional SAM2 post-processing.
: "${SEGMENTATION_DATASETS:=eval_seg_refcoco,eval_seg_refcocop,eval_seg_refcocog,eval_seg_mevis,eval_seg_reasonvos}"
: "${SEGMENTATION_BENCH_DIR:=${PROJECT_DIR}/data/eval/segmentation}"
: "${SEGMENTATION_DATA_ROOT:=$SEGMENTATION_BENCH_DIR}"
: "${SEGMENTATION_PROCESSOR_PATH:=$MODEL_PATH}"
: "${SEGMENTATION_DATA_TYPE:=all}"
# train_seg mirrors the prompt used in joint SFT training data
# (data/train/seg_image_nothink_evalaware.jsonl, seg_video_nothink.jsonl).
: "${SEGMENTATION_PROMPT_MODE:=train_seg}"
: "${SEGMENTATION_ENABLE_THINKING:=false}"
: "${SEGMENTATION_BATCH_SIZE:=16}"
: "${SEGMENTATION_MAX_NEW_TOKENS:=1024}"
: "${SEGMENTATION_MAX_MODEL_LEN:=32768}"
: "${SEGMENTATION_MAX_PIXELS_IMAGE:=1048576}"
: "${SEGMENTATION_MIN_PIXELS_IMAGE:=4096}"
: "${SEGMENTATION_VIDEO_MAX_PIXELS:=262144}"
: "${SEGMENTATION_VIDEO_MIN_PIXELS:=4096}"
: "${SEGMENTATION_VIDEO_TOTAL_PIXELS:=16777216}"
: "${SEGMENTATION_MAX_FRAMES:=128}"
: "${SEGMENTATION_FPS:=2}"
: "${SEGMENTATION_VIDEO_READER:=decord}"
: "${SEGMENTATION_GPU_MEM_UTIL:=0.85}"
: "${SEGMENTATION_SEED:=42}"
: "${SEGMENTATION_MAX_SAMPLES:=}"
: "${SEGMENTATION_RUN_SAM2:=false}"
: "${SEGMENTATION_SAM2_CKPT:=${PROJECT_DIR}/models/sam2/sam2.1_hiera_large.pt}"
: "${SEGMENTATION_SAM2_CFG:=configs/sam2.1/sam2.1_hiera_l.yaml}"
: "${SEGMENTATION_POSTPROCESSOR_PATH:=${PROJECT_DIR}/third_party/OneThinker/Evaluation/Eval/seg_post_sam2.py}"
# SAM2 post-processing parallelism. world_size = NUM_GPUS * WORKERS_PER_GPU.
# With a large SAM2_EPOCH_SIZE (single epoch) + maxtasksperchild=1, EACH worker
# loads the SAM2 model exactly ONCE at startup and then streams its whole slice
# (no repeated reloads). So WORKERS_PER_GPU only trades GPU utilization vs total
# process count: too high (32 -> 256 procs) exhausts CPU/RAM/ffmpeg/handles and
# aborts; too low (1) underutilizes the GPU. 4 per GPU is a balance (8 GPUs -> 32
# persistent workers, 32 one-time loads); bump to 6-8 if GPU is still not full.
# Leave NUM_GPUS empty to auto-use all visible GPUs.
: "${SEGMENTATION_SAM2_NUM_GPUS:=}"
: "${SEGMENTATION_SAM2_WORKERS_PER_GPU:=8}"
: "${SEGMENTATION_SETTING:=segmentation-${SEGMENTATION_DATASETS//,/_}-${SEGMENTATION_PROMPT_MODE}-f${SEGMENTATION_MAX_FRAMES}-fps${SEGMENTATION_FPS}-min${SEGMENTATION_VIDEO_MIN_PIXELS}-max${SEGMENTATION_VIDEO_MAX_PIXELS}-total${SEGMENTATION_VIDEO_TOTAL_PIXELS}-new${SEGMENTATION_MAX_NEW_TOKENS}}"
# TimeLens-Bench temporal grounding defaults.
# This task uses HuggingFace transformers, not vLLM.
: "${TIMELENS_DATASETS:=charades-timelens}"
: "${TIMELENS_BENCH_DIR:=${PROJECT_DIR}/data/eval/temporal_grounding}"
: "${TIMELENS_ENABLE_THINKING:=false}"
: "${TIMELENS_MIN_TOKENS:=1}"
: "${TIMELENS_TOTAL_TOKENS:=128000}"
: "${TIMELENS_MAX_PIXELS:=409600}"
: "${TIMELENS_MAX_FRAMES:=2048}"
: "${TIMELENS_FPS:=4}"
: "${TIMELENS_MAX_NEW_TOKENS:=128}"
: "${TIMELENS_REPETITION_PENALTY:=1.0}"
: "${TIMELENS_STOP_AFTER_ANSWER:=true}"
: "${TIMELENS_PROMPT_MODE:=same}"
: "${TIMELENS_NUM_WORKERS:=2}"
: "${TIMELENS_MAX_SAMPLES:=0}"
export MODEL_PATH TASKS GPUS TP_SIZE SHARD_MODE VIDEO_CACHE_SIZE PREFETCH_BATCHES
export FORCE_MERGE SKIP_MERGE MERGE_LOG_DIR
export VIDEOMME_SETTING VIDEOMME_DATA_FILE VIDEOMME_VIDEO_BASE VIDEOMME_VIDEO_DIR
export VIDEOMME_PREPROCESSED_VIDEO_DIR VIDEOMME_VIDEO_MIN_PIXELS VIDEOMME_VIDEO_MAX_PIXELS
export VIDEOMME_VIDEO_TOTAL_PIXELS VIDEOMME_MAX_FRAMES VIDEOMME_FPS
export VIDEOMME_BATCH_SIZE VIDEOMME_MAX_MODEL_LEN VIDEOMME_MAX_NEW_TOKENS
export VIDEOMME_MAX_NUM_BATCHED_TOKENS VIDEOMME_GPU_MEMORY_UTILIZATION
export VIDEOMME_MAX_SAMPLES
export VIDEOMMEV2_SETTING VIDEOMMEV2_DATA_FILE VIDEOMMEV2_VIDEO_BASE VIDEOMMEV2_VIDEO_DIR
export VIDEOMMEV2_PREPROCESSED_VIDEO_DIR VIDEOMMEV2_VIDEO_MIN_PIXELS VIDEOMMEV2_VIDEO_MAX_PIXELS
export VIDEOMMEV2_VIDEO_TOTAL_PIXELS VIDEOMMEV2_MAX_FRAMES VIDEOMMEV2_FPS
export VIDEOMMEV2_BATCH_SIZE VIDEOMMEV2_MAX_MODEL_LEN VIDEOMMEV2_MAX_NEW_TOKENS
export VIDEOMMEV2_MAX_NUM_BATCHED_TOKENS VIDEOMMEV2_GPU_MEMORY_UTILIZATION
export VIDEOMMEV2_PROMPT_MODE VIDEOMMEV2_ANSWER_FILTER VIDEOMMEV2_MAX_SAMPLES
export VIDEOMMMU_SETTING VIDEOMMMU_DATA_FILE VIDEOMMMU_VIDEO_ROOT
export VIDEOMMMU_BATCH_SIZE VIDEOMMMU_MAX_MODEL_LEN VIDEOMMMU_MAX_NEW_TOKENS
export VIDEOMMMU_MAX_NUM_BATCHED_TOKENS VIDEOMMMU_GPU_MEMORY_UTILIZATION
export VIDEOMMMU_VIDEO_MIN_PIXELS VIDEOMMMU_VIDEO_MAX_PIXELS VIDEOMMMU_VIDEO_TOTAL_PIXELS
export VIDEOMMMU_MAX_FRAMES VIDEOMMMU_FPS VIDEOMMMU_PROMPT_MODE VIDEOMMMU_IMAGE_MAX_PIXELS
export VIDEOMMMU_ENABLE_THINKING VIDEOMMMU_TEMPERATURE VIDEOMMMU_TOP_P VIDEOMMMU_TOP_K
export VIDEOMMMU_PRESENCE_PENALTY VIDEOMMMU_MIN_P
export MMVU_SETTING MMVU_DATA_FILE MMVU_VIDEO_ROOT MMVU_BATCH_SIZE
export MMVU_MAX_MODEL_LEN MMVU_MAX_NEW_TOKENS MMVU_MAX_NUM_BATCHED_TOKENS
export MMVU_GPU_MEMORY_UTILIZATION MMVU_VIDEO_MIN_PIXELS MMVU_VIDEO_MAX_PIXELS
export MMVU_VIDEO_TOTAL_PIXELS MMVU_MAX_FRAMES MMVU_FPS MMVU_PROMPT_MODE
export MMVU_ENABLE_THINKING MMVU_TEMPERATURE MMVU_TOP_P MMVU_TOP_K
export MMVU_PRESENCE_PENALTY MMVU_MIN_P MMVU_MAX_SAMPLES
export MVBENCH_SETTING MVBENCH_DATA_FILE MVBENCH_VIDEO_ROOT MVBENCH_BATCH_SIZE
export MVBENCH_MAX_MODEL_LEN MVBENCH_MAX_NEW_TOKENS MVBENCH_MAX_NUM_BATCHED_TOKENS
export MVBENCH_GPU_MEMORY_UTILIZATION MVBENCH_VIDEO_MIN_PIXELS MVBENCH_VIDEO_MAX_PIXELS
export MVBENCH_VIDEO_TOTAL_PIXELS MVBENCH_MAX_FRAMES MVBENCH_FPS MVBENCH_PROMPT_MODE
export MVBENCH_ENABLE_THINKING MVBENCH_TEMPERATURE MVBENCH_TOP_P MVBENCH_TOP_K
export MVBENCH_PRESENCE_PENALTY MVBENCH_MIN_P MVBENCH_MAX_SAMPLES
export VIDEOHOLMES_SETTING VIDEOHOLMES_DATA_FILE VIDEOHOLMES_VIDEO_ROOT VIDEOHOLMES_BATCH_SIZE
export VIDEOHOLMES_MAX_MODEL_LEN VIDEOHOLMES_MAX_NEW_TOKENS VIDEOHOLMES_MAX_NUM_BATCHED_TOKENS
export VIDEOHOLMES_GPU_MEMORY_UTILIZATION VIDEOHOLMES_VIDEO_MIN_PIXELS VIDEOHOLMES_VIDEO_MAX_PIXELS
export VIDEOHOLMES_VIDEO_TOTAL_PIXELS VIDEOHOLMES_MAX_FRAMES VIDEOHOLMES_FPS VIDEOHOLMES_PROMPT_MODE
export VIDEOHOLMES_ENABLE_THINKING VIDEOHOLMES_TEMPERATURE VIDEOHOLMES_TOP_P VIDEOHOLMES_TOP_K
export VIDEOHOLMES_PRESENCE_PENALTY VIDEOHOLMES_MIN_P VIDEOHOLMES_MAX_SAMPLES
export LONGVIDEOBENCH_SETTING LONGVIDEOBENCH_DATA_FILE LONGVIDEOBENCH_VIDEO_ROOT
export LONGVIDEOBENCH_SUBTITLE_ROOT LONGVIDEOBENCH_USE_SUBTITLES LONGVIDEOBENCH_BATCH_SIZE
export LONGVIDEOBENCH_MAX_MODEL_LEN LONGVIDEOBENCH_MAX_NEW_TOKENS LONGVIDEOBENCH_MAX_NUM_BATCHED_TOKENS
export LONGVIDEOBENCH_GPU_MEMORY_UTILIZATION LONGVIDEOBENCH_VIDEO_MIN_PIXELS LONGVIDEOBENCH_VIDEO_MAX_PIXELS
export LONGVIDEOBENCH_VIDEO_TOTAL_PIXELS LONGVIDEOBENCH_MAX_FRAMES LONGVIDEOBENCH_FPS LONGVIDEOBENCH_PROMPT_MODE
export LONGVIDEOBENCH_ENABLE_THINKING LONGVIDEOBENCH_TEMPERATURE LONGVIDEOBENCH_TOP_P LONGVIDEOBENCH_TOP_K
export LONGVIDEOBENCH_PRESENCE_PENALTY LONGVIDEOBENCH_MIN_P LONGVIDEOBENCH_MAX_SAMPLES
export LVBENCH_SETTING LVBENCH_DATA_FILE LVBENCH_VIDEO_ROOT LVBENCH_BATCH_SIZE
export LVBENCH_MAX_MODEL_LEN LVBENCH_MAX_NEW_TOKENS LVBENCH_MAX_NUM_BATCHED_TOKENS
export LVBENCH_GPU_MEMORY_UTILIZATION LVBENCH_VIDEO_MIN_PIXELS LVBENCH_VIDEO_MAX_PIXELS
export LVBENCH_VIDEO_TOTAL_PIXELS LVBENCH_MAX_FRAMES LVBENCH_FPS LVBENCH_PROMPT_MODE
export LVBENCH_ENABLE_THINKING LVBENCH_TEMPERATURE LVBENCH_TOP_P LVBENCH_TOP_K
export LVBENCH_PRESENCE_PENALTY LVBENCH_MIN_P
export MLVU_SETTING MLVU_DATA_FILE MLVU_VIDEO_ROOT MLVU_BATCH_SIZE
export MLVU_MAX_MODEL_LEN MLVU_MAX_NEW_TOKENS MLVU_MAX_NUM_BATCHED_TOKENS
export MLVU_GPU_MEMORY_UTILIZATION MLVU_VIDEO_MIN_PIXELS MLVU_VIDEO_MAX_PIXELS
export MLVU_VIDEO_TOTAL_PIXELS MLVU_MAX_FRAMES MLVU_FPS MLVU_PROMPT_MODE
export MLVU_ENABLE_THINKING MLVU_TEMPERATURE MLVU_TOP_P MLVU_TOP_K
export MLVU_PRESENCE_PENALTY MLVU_MIN_P MLVU_MAX_SAMPLES
export VSI_SETTING VSI_DATA_FILE VSI_PREPROCESSED_VIDEO_DIR
export VSI_BATCH_SIZE VSI_MAX_MODEL_LEN VSI_MAX_NEW_TOKENS VSI_GPU_MEMORY_UTILIZATION
export VSI_EXPECTED_SAMPLES
export MMSI_BACKEND MMSI_SETTING MMSI_DATA_FILE MMSI_MAX_IMAGES MMSI_BATCH_SIZE
export MMSI_IMAGE_MIN_PIXELS MMSI_IMAGE_MAX_PIXELS MMSI_IMAGE_COUNT_TAG
export MMSI_MAX_MODEL_LEN MMSI_MAX_NEW_TOKENS MMSI_MAX_NUM_BATCHED_TOKENS
export MMSI_GPU_MEMORY_UTILIZATION MMSI_MAX_SAMPLES MMSI_CATEGORY
export MMSI_ENABLE_THINKING MMSI_ATTN_IMPLEMENTATION MMSI_EXPECTED_SAMPLES
export MINDCUBE_SETTING MINDCUBE_DATA_FILE MINDCUBE_MAX_IMAGES MINDCUBE_BATCH_SIZE
export MINDCUBE_MAX_MODEL_LEN MINDCUBE_MAX_NEW_TOKENS MINDCUBE_MAX_NUM_BATCHED_TOKENS
export MINDCUBE_GPU_MEMORY_UTILIZATION MINDCUBE_EXPECTED_SAMPLES MINDCUBE_HF_CACHE_DIR
export REVSI_SETTING REVSI_DATA_FILE REVSI_VIDEO_ROOT REVSI_FRAME_BUDGET
export REVSI_MAX_FRAMES REVSI_EXACT_NFRAMES REVSI_FPS
export REVSI_VIDEO_MIN_PIXELS REVSI_VIDEO_MAX_PIXELS REVSI_VIDEO_TOTAL_PIXELS
export REVSI_BATCH_SIZE REVSI_MAX_MODEL_LEN REVSI_MAX_NEW_TOKENS
export REVSI_GPU_MEMORY_UTILIZATION REVSI_MAX_SAMPLES REVSI_EXPECTED_SAMPLES
export REVSI_TASK_FILTER REVSI_ENABLE_THINKING
export SPATIAL_GROUNDING_SETTING SPATIAL_GROUNDING_DATASETS SPATIAL_GROUNDING_BENCH_DIR
export SPATIAL_GROUNDING_IMAGE_ROOT SPATIAL_GROUNDING_PROCESSOR_PATH SPATIAL_GROUNDING_PROMPT_STYLE
export SPATIAL_GROUNDING_COORD_SYSTEM SPATIAL_GROUNDING_BBOX_SELECT
export SPATIAL_GROUNDING_MIN_TOKENS SPATIAL_GROUNDING_TOTAL_TOKENS
export SPATIAL_GROUNDING_BATCH_SIZE SPATIAL_GROUNDING_MAX_MODEL_LEN
export SPATIAL_GROUNDING_MAX_NEW_TOKENS SPATIAL_GROUNDING_MAX_NUM_BATCHED_TOKENS
export SPATIAL_GROUNDING_GPU_MEMORY_UTILIZATION SPATIAL_GROUNDING_ENABLE_THINKING
export SPATIAL_GROUNDING_MAX_SAMPLES
export TRACKING_SETTING TRACKING_DATASETS TRACKING_BENCH_DIR TRACKING_BASE_PREFIX
export TRACKING_PROCESSOR_PATH TRACKING_VIDEO_MIN_PIXELS TRACKING_VIDEO_MAX_PIXELS
export TRACKING_VIDEO_TOTAL_PIXELS TRACKING_MAX_FRAMES TRACKING_FPS
export TRACKING_MAX_MODEL_LEN TRACKING_MAX_NEW_TOKENS TRACKING_MAX_NUM_BATCHED_TOKENS
export TRACKING_BATCH_SIZE TRACKING_GPU_MEMORY_UTILIZATION TRACKING_ENABLE_THINKING
export TRACKING_PROMPT_MODE TRACKING_CHUNKED_REPROMPT TRACKING_REPROMPT_USE_GT_FIRST_BOX
export TRACKING_MAX_SAMPLES
export STVG_SETTING STVG_DATASETS STVG_BENCH_DIR STVG_BASE_PREFIX STVG_PROCESSOR_PATH
export STVG_VIDEO_MIN_PIXELS STVG_VIDEO_MAX_PIXELS STVG_VIDEO_TOTAL_PIXELS
export STVG_MAX_FRAMES STVG_FPS STVG_MAX_MODEL_LEN STVG_MAX_NEW_TOKENS
export STVG_MAX_NUM_BATCHED_TOKENS STVG_BATCH_SIZE STVG_GPU_MEMORY_UTILIZATION
export STVG_ENABLE_THINKING STVG_PROMPT_MODE STVG_MAX_SAMPLES
export SEGMENTATION_SETTING SEGMENTATION_DATASETS SEGMENTATION_BENCH_DIR SEGMENTATION_DATA_ROOT
export SEGMENTATION_PROCESSOR_PATH SEGMENTATION_DATA_TYPE SEGMENTATION_PROMPT_MODE
export SEGMENTATION_ENABLE_THINKING SEGMENTATION_BATCH_SIZE SEGMENTATION_MAX_NEW_TOKENS
export SEGMENTATION_MAX_MODEL_LEN SEGMENTATION_MAX_PIXELS_IMAGE SEGMENTATION_MIN_PIXELS_IMAGE
export SEGMENTATION_VIDEO_MAX_PIXELS SEGMENTATION_VIDEO_MIN_PIXELS SEGMENTATION_VIDEO_TOTAL_PIXELS
export SEGMENTATION_MAX_FRAMES SEGMENTATION_FPS SEGMENTATION_VIDEO_READER
export SEGMENTATION_GPU_MEM_UTIL SEGMENTATION_SEED
export SEGMENTATION_MAX_SAMPLES
export SEGMENTATION_RUN_SAM2 SEGMENTATION_SAM2_CKPT SEGMENTATION_SAM2_CFG
export SEGMENTATION_SAM2_NUM_GPUS SEGMENTATION_SAM2_WORKERS_PER_GPU
export TIMELENS_BENCH_DIR TIMELENS_MAX_SAMPLES
# Conda env used to run eval. By default, keep the currently active environment.
# Override with EVAL_CONDA_ENV=xxx only when an explicit env switch is desired.
: "${EVAL_CONDA_ENV:=keep}"
if [[ "${EVAL_CONDA_ENV}" != "keep" && "${CONDA_DEFAULT_ENV:-}" != "${EVAL_CONDA_ENV}" ]]; then
if command -v conda >/dev/null 2>&1; then
eval "$(conda shell.bash hook)"
conda activate "${EVAL_CONDA_ENV}"
else
echo "ERROR: conda not found and CONDA_DEFAULT_ENV=${CONDA_DEFAULT_ENV:-<unset>}" >&2
exit 1
fi
fi
cd "${PROJECT_DIR}"
resolve_model_path() {
local input_path="${MODEL_PATH%/}"
if ls "${input_path}"/model_world_size_*_rank_0.pt >/dev/null 2>&1; then
local actor_dir="$input_path"
local hf_dir="${MERGED_MODEL_PATH:-${actor_dir}/huggingface}"
local need_merge=0
if [[ "${SKIP_MERGE}" = "1" ]]; then
need_merge=0
elif [[ "${FORCE_MERGE}" = "1" ]]; then
need_merge=1
elif [[ ! -f "${hf_dir}/model.safetensors" ]]; then
need_merge=1
fi
if [[ "${need_merge}" = "1" ]]; then
mkdir -p "${MERGE_LOG_DIR}"
local merge_log="${MERGE_LOG_DIR}/merge-$(basename "$(dirname "${actor_dir}")")-$(date +%Y%m%d_%H%M%S).log"
echo "[merge] FSDP actor checkpoint detected: ${actor_dir}"
echo "[merge] Merging shards -> ${hf_dir}"
if [[ -n "${BASE_MODEL_PATH:-}" ]]; then
python -u scripts/model_merger.py \
--local_dir "${actor_dir}" \
--base_model_path "${BASE_MODEL_PATH}" \
2>&1 | tee "${merge_log}"
else
python -u scripts/model_merger.py \
--local_dir "${actor_dir}" \
2>&1 | tee "${merge_log}"
fi
if [[ ! -f "${hf_dir}/model.safetensors" ]]; then
echo "ERROR: merge finished but ${hf_dir}/model.safetensors was not created. Log: ${merge_log}" >&2
exit 1
fi
else
echo "[merge] Using existing merged HF model: ${hf_dir}"
fi
MODEL_PATH="${hf_dir}"
export MODEL_PATH
if [[ "${TRACKING_PROCESSOR_PATH%/}" = "${input_path}" ]]; then
TRACKING_PROCESSOR_PATH="${MODEL_PATH}"
export TRACKING_PROCESSOR_PATH
fi
if [[ "${STVG_PROCESSOR_PATH%/}" = "${input_path}" ]]; then
STVG_PROCESSOR_PATH="${MODEL_PATH}"
export STVG_PROCESSOR_PATH
fi
if [[ "${SPATIAL_GROUNDING_PROCESSOR_PATH%/}" = "${input_path}" ]]; then
SPATIAL_GROUNDING_PROCESSOR_PATH="${MODEL_PATH}"
export SPATIAL_GROUNDING_PROCESSOR_PATH
fi
if [[ "${SEGMENTATION_PROCESSOR_PATH%/}" = "${input_path}" ]]; then
SEGMENTATION_PROCESSOR_PATH="${MODEL_PATH}"
export SEGMENTATION_PROCESSOR_PATH
fi
elif [[ -d "${input_path}/huggingface" && -f "${input_path}/huggingface/model.safetensors" && ! -f "${input_path}/config.json" ]]; then
MODEL_PATH="${input_path}/huggingface"
export MODEL_PATH
echo "[merge] MODEL_PATH points to a checkpoint wrapper; using ${MODEL_PATH}"
fi
}
resolve_model_path
VLLM_TASKS=""
RUN_TIMELENS=0
RUN_SEGMENTATION=0
RUN_MMSI_TRANSFORMERS=0
RUN_REVSI=0
if [[ "${MMSI_BACKEND}" != "transformers" && "${MMSI_BACKEND}" != "vllm" ]]; then
echo "ERROR: MMSI_BACKEND must be 'transformers' or 'vllm', got '${MMSI_BACKEND}'" >&2
exit 1
fi
append_vllm_task() {
local task="$1"
if [[ -z "$VLLM_TASKS" ]]; then
VLLM_TASKS="$task"
else
VLLM_TASKS="${VLLM_TASKS},${task}"
fi
}
model_family_tag() {
local model_path="${1%/}"
local name
name="$(basename "$model_path")"
local parent
local grandparent
parent="$(basename "$(dirname "$model_path")")"
grandparent="$(basename "$(dirname "$(dirname "$model_path")")")"
if [[ "$name" == "huggingface" && "$parent" == "actor" && "$grandparent" == global_step_* ]]; then
basename "$(dirname "$(dirname "$(dirname "$model_path")")")"
return
fi
if [[ "$name" == checkpoint-* ]]; then
basename "$(dirname "$(dirname "$model_path")")"
else
echo "$name"
fi
}
checkpoint_tag() {
local model_path="${1%/}"
local name
name="$(basename "$model_path")"
local parent
local grandparent
parent="$(basename "$(dirname "$model_path")")"
grandparent="$(basename "$(dirname "$(dirname "$model_path")")")"
if [[ "$name" == "huggingface" && "$parent" == "actor" && "$grandparent" == global_step_* ]]; then
basename "$(dirname "$(dirname "$model_path")")"
return
fi
if [[ "$name" == checkpoint-* ]]; then
echo "$name"
else
echo "base"
fi
}
IFS=',' read -ra TASK_LIST <<< "$TASKS"
for RAW_TASK in "${TASK_LIST[@]}"; do
TASK="$(echo "$RAW_TASK" | xargs)"
case "$TASK" in
all)
VLLM_TASKS="videomme,videommev2,videommmu,mmvu,mvbench,videoholmes,longvideobench,lvbench,mlvu,vsi,mindcube,spatial_grounding,tracking,stvg"
if [[ "${MMSI_BACKEND}" == "transformers" ]]; then
RUN_MMSI_TRANSFORMERS=1
else
append_vllm_task "mmsi"
fi
RUN_REVSI=1
;;
videomme|videommev2|videommmu|mmvu|mvbench|videoholmes|longvideobench|lvbench|mlvu|vsi|mindcube|spatial_grounding|tracking|stvg)
append_vllm_task "$TASK"
;;
mmsi)
if [[ "${MMSI_BACKEND}" == "transformers" ]]; then
RUN_MMSI_TRANSFORMERS=1
else
append_vllm_task "mmsi"
fi
;;
revsi)
RUN_REVSI=1
;;
spatial|grounding|refcoco|spatial_grounding_eval)
append_vllm_task "spatial_grounding"
;;
spatial_temporal_grounding)
append_vllm_task "stvg"
;;
temporal_grounding|timelens|timelens_bench)
RUN_TIMELENS=1
;;
segmentation|seg|reasonseg|refseg)
RUN_SEGMENTATION=1
;;
"")
;;
*)
echo "ERROR: unknown TASK '${TASK}'. Supported: videomme,videommev2,videommmu,mmvu,mvbench,videoholmes,longvideobench,lvbench,mlvu,vsi,mmsi,mindcube,revsi,spatial_grounding,tracking,stvg,temporal_grounding,segmentation,all" >&2
exit 1
;;
esac
done
if [[ -n "$VLLM_TASKS" ]]; then
TASKS="$VLLM_TASKS" python eval/task/eval_vllm.py "$@"
fi
if [[ "$RUN_MMSI_TRANSFORMERS" = "1" ]]; then
MMSI_FAMILY="$(model_family_tag "$MODEL_PATH")"
MMSI_CKPT="$(checkpoint_tag "$MODEL_PATH")"
MMSI_RUN_ROOT="${PROJECT_DIR}/outputs/${MMSI_FAMILY}/spatial_intelligence/mmsi/${MMSI_CKPT}/${MMSI_SETTING}/$(date +%Y%m%d_%H%M%S)"
CUDA_VISIBLE_DEVICES="$GPUS" \
PROCESSOR_PATH="$MODEL_PATH" \
DATA_FILE="$MMSI_DATA_FILE" \
OUTPUT_DIR="$MMSI_RUN_ROOT" \
IMAGE_MIN_PIXELS="$MMSI_IMAGE_MIN_PIXELS" \
IMAGE_MAX_PIXELS="$MMSI_IMAGE_MAX_PIXELS" \
MAX_IMAGES="$MMSI_MAX_IMAGES" \
MAX_NEW_TOKENS="$MMSI_MAX_NEW_TOKENS" \
MAX_SAMPLES="$MMSI_MAX_SAMPLES" \
CATEGORY="$MMSI_CATEGORY" \
ENABLE_THINKING="$MMSI_ENABLE_THINKING" \
ATTN_IMPLEMENTATION="$MMSI_ATTN_IMPLEMENTATION" \
EXPECTED_SAMPLES="$MMSI_EXPECTED_SAMPLES" \
bash eval/task/mmsi/run_eval_transformers.sh "$MODEL_PATH"
fi
if [[ "$RUN_REVSI" = "1" ]]; then
REVSI_FAMILY="$(model_family_tag "$MODEL_PATH")"
REVSI_CKPT="$(checkpoint_tag "$MODEL_PATH")"
REVSI_RUN_EXPECTED_SAMPLES="$REVSI_EXPECTED_SAMPLES"
if [[ "$REVSI_MAX_SAMPLES" != "0" || -n "$REVSI_TASK_FILTER" ]]; then
REVSI_RUN_EXPECTED_SAMPLES=0
fi
REVSI_RUN_ROOT="${PROJECT_DIR}/outputs/${REVSI_FAMILY}/spatial_intelligence/revsi/${REVSI_CKPT}/${REVSI_SETTING}/$(date +%Y%m%d_%H%M%S)"
CUDA_VISIBLE_DEVICES="$GPUS" \
REVSI_ROOT="$REVSI_VIDEO_ROOT" \
QA_FILE="$REVSI_DATA_FILE" \
VIDEO_ROOT="$REVSI_VIDEO_ROOT" \
FRAME_BUDGET="$REVSI_FRAME_BUDGET" \
OUTPUT_DIR="$REVSI_RUN_ROOT" \
MAX_FRAMES="$REVSI_MAX_FRAMES" \
EXACT_NFRAMES="$REVSI_EXACT_NFRAMES" \
FPS="$REVSI_FPS" \
VIDEO_MIN_PIXELS="$REVSI_VIDEO_MIN_PIXELS" \
VIDEO_MAX_PIXELS="$REVSI_VIDEO_MAX_PIXELS" \
VIDEO_TOTAL_PIXELS="$REVSI_VIDEO_TOTAL_PIXELS" \
BATCH_SIZE="$REVSI_BATCH_SIZE" \
MAX_MODEL_LEN="$REVSI_MAX_MODEL_LEN" \
MAX_NEW_TOKENS="$REVSI_MAX_NEW_TOKENS" \
GPU_MEM_UTIL="$REVSI_GPU_MEMORY_UTILIZATION" \
MAX_SAMPLES="$REVSI_MAX_SAMPLES" \
EXPECTED_SAMPLES="$REVSI_RUN_EXPECTED_SAMPLES" \
TASK_FILTER="$REVSI_TASK_FILTER" \
ENABLE_THINKING="$REVSI_ENABLE_THINKING" \
TP_SIZE="$TP_SIZE" \
bash eval/task/revsi/run_eval_vllm.sh "$MODEL_PATH"
fi
if [[ "$RUN_TIMELENS" = "1" ]]; then
TIMELENS_FAMILY="$(model_family_tag "$MODEL_PATH")"
TIMELENS_CKPT="$(checkpoint_tag "$MODEL_PATH")"
TIMELENS_SETTING="timelens-fps${TIMELENS_FPS}-min${TIMELENS_MIN_TOKENS}-total${TIMELENS_TOTAL_TOKENS}-new${TIMELENS_MAX_NEW_TOKENS}-${TIMELENS_DATASETS//,/_}"
TIMELENS_RUN_ROOT="${PROJECT_DIR}/outputs/${TIMELENS_FAMILY}/temporal_grounding/${TIMELENS_CKPT}/${TIMELENS_SETTING}/$(date +%Y%m%d_%H%M%S)"
CUDA_VISIBLE_DEVICES="$GPUS" \
DATASETS="$TIMELENS_DATASETS" \
SETTING="$TIMELENS_SETTING" \
OUTPUT_ROOT="$TIMELENS_RUN_ROOT" \
TIMELENS_USE_OUTPUT_ROOT_DIRECT=1 \
MIN_TOKENS="$TIMELENS_MIN_TOKENS" \
TOTAL_TOKENS="$TIMELENS_TOTAL_TOKENS" \
MAX_PIXELS="$TIMELENS_MAX_PIXELS" \
MAX_FRAMES="$TIMELENS_MAX_FRAMES" \
FPS="$TIMELENS_FPS" \
MAX_NEW_TOKENS="$TIMELENS_MAX_NEW_TOKENS" \
REPETITION_PENALTY="$TIMELENS_REPETITION_PENALTY" \
STOP_AFTER_ANSWER="$TIMELENS_STOP_AFTER_ANSWER" \
PROMPT_MODE="$TIMELENS_PROMPT_MODE" \
NUM_WORKERS="$TIMELENS_NUM_WORKERS" \
bash eval/task/temporal_grounding/run_eval.sh \
"$MODEL_PATH" \
"$TIMELENS_ENABLE_THINKING" \
"$TIMELENS_RUN_ROOT"
fi
if [[ "$RUN_SEGMENTATION" = "1" ]]; then
SEG_FAMILY="$(model_family_tag "$MODEL_PATH")"
SEG_CKPT="$(checkpoint_tag "$MODEL_PATH")"
SEG_RUN_ROOT="${PROJECT_DIR}/outputs/${SEG_FAMILY}/segmentation/${SEG_CKPT}/${SEGMENTATION_SETTING}/$(date +%Y%m%d_%H%M%S)"
CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-$GPUS}" \
PROCESSOR_PATH="$SEGMENTATION_PROCESSOR_PATH" \
BENCH_DIR="$SEGMENTATION_BENCH_DIR" \
DATA_ROOT="$SEGMENTATION_DATA_ROOT" \
DATASETS="$SEGMENTATION_DATASETS" \
DATA_TYPE="$SEGMENTATION_DATA_TYPE" \
PROMPT_MODE="$SEGMENTATION_PROMPT_MODE" \
ENABLE_THINKING="$SEGMENTATION_ENABLE_THINKING" \
BATCH_SIZE="$SEGMENTATION_BATCH_SIZE" \
MAX_NEW_TOKENS="$SEGMENTATION_MAX_NEW_TOKENS" \
MAX_MODEL_LEN="$SEGMENTATION_MAX_MODEL_LEN" \
MAX_PIXELS_IMAGE="$SEGMENTATION_MAX_PIXELS_IMAGE" \
MIN_PIXELS_IMAGE="$SEGMENTATION_MIN_PIXELS_IMAGE" \
VIDEO_MAX_PIXELS="$SEGMENTATION_VIDEO_MAX_PIXELS" \
VIDEO_MIN_PIXELS="$SEGMENTATION_VIDEO_MIN_PIXELS" \
VIDEO_TOTAL_PIXELS="$SEGMENTATION_VIDEO_TOTAL_PIXELS" \
MAX_FRAMES="$SEGMENTATION_MAX_FRAMES" \
FPS="$SEGMENTATION_FPS" \
VIDEO_READER="$SEGMENTATION_VIDEO_READER" \
TP_SIZE="$TP_SIZE" \
GPU_MEM_UTIL="$SEGMENTATION_GPU_MEM_UTIL" \
SEED="$SEGMENTATION_SEED" \
MAX_SAMPLES="$SEGMENTATION_MAX_SAMPLES" \
RUN_SAM2="$SEGMENTATION_RUN_SAM2" \
SAM2_CKPT="$SEGMENTATION_SAM2_CKPT" \
SAM2_CFG="$SEGMENTATION_SAM2_CFG" \
ONETHINKER_SEG_POST="$SEGMENTATION_POSTPROCESSOR_PATH" \
SAM2_NUM_GPUS="$SEGMENTATION_SAM2_NUM_GPUS" \
SAM2_WORKERS_PER_GPU="$SEGMENTATION_SAM2_WORKERS_PER_GPU" \
bash eval/task/segmentation/run_eval_vllm.sh \
"$MODEL_PATH" \
"$SEG_RUN_ROOT"
fi
|