fishxinyu/LTX-2 / cmd /batch_eval /flexbench_eval_lora_switch.sh
fishxinyu's picture
download
raw
1.36 kB
#!/bin/bash
export CUDA_VISIBLE_DEVICES=3
cd ~/flexvideo/LTX-2
source ~/flexvideo/LTX-2/.venv/bin/activate
for TASK in subject_pose subject_depth subject_inpainting pose_inpainting; do
EXTRA_ARGS=(--subject-offset-frames 100)
if [ "$TASK" == "pose_inpainting" ]; then
EXTRA_ARGS=()
fi
python -m packages.ltx-pipelines.src.ltx_pipelines.flexbench_inference \
--distilled-checkpoint-path /home/xinyuy/flexvideo/LTX-2/ckpts/LTX-2.3/ltx-2.3-22b-distilled.safetensors \
--spatial-upsampler-path /home/xinyuy/flexvideo/LTX-2/ckpts/LTX-2.3/ltx-2.3-spatial-upscaler-x2-1.0.safetensors \
--gemma-root /mnt/data/xinyuy/models/Gemma3 \
--dataset-dir /home/xinyuy/dataset_processing/flexcombine-bench/datasets/v0/${TASK} \
--output-dir /home/xinyuy/dataset_processing/flexcombine-bench/results/flexbench/v0_scale_up/lora-switch/${TASK} \
--hub-dir /home/xinyuy/flexvideo/LTX-2/outputs_scale_up_1gpu/hub \
--mode lora-switch \
--skip-stage-2 \
--show-conditioning \
--frame-num 81 \
--seeds-n 5 \
"${EXTRA_ARGS[@]}"
done
deactivate
cd ~/dataset_processing/flexcombine-bench
for TASK in subject_pose subject_depth subject_inpainting pose_inpainting; do
evaluation/run_eval.sh --generated-dir results/flexbench/v0_scale_up/lora-switch/${TASK}
done

Xet Storage Details

Size:
1.36 kB
·
Xet hash:
33ebdafb19157aac3cc38b1a695201f4d2434fb56961a4db196545b958bedb88

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.