3.1 KiB
3.1 KiB
office_vlm 预训练权重(vendor 共享)
vlm_detection / semantic_nav 首次运行会拉取约 500MB 权重。放入 JuiceFS vendor 后,各用户 workspace 通过 setup_model_cache.sh 幂等软链到 ~/.cache,避免重复下载。
模型与下载地址
| 用途 | 代码 | 文件名 | 约大小 | 下载 URL |
|---|---|---|---|---|
| Faster R-CNN v2 | fasterrcnn_resnet50_fpn_v2(weights="DEFAULT") |
fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth |
~167 MB | https://download.pytorch.org/models/fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth |
| CLIP ViT-B/32 | clip.load("ViT-B/32") |
ViT-B-32.pt |
~338 MB | https://openaipublic.azureedge.net/clip/models/40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af/ViT-B-32.pt |
CLIP 校验 SHA256:40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af
本地打包目录示例(上传前):
office_vlm_models/
├── torch/hub/checkpoints/
│ └── fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth
└── clip/
└── ViT-B-32.pt
vendor 卷内路径(容器内 /opt/vendor)
/opt/vendor/models/office_vlm/
├── torch/hub/checkpoints/fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth
└── clip/ViT-B-32.pt
运行时缓存(软链目标):
| 框架 | 路径 |
|---|---|
| torchvision | ~/.cache/torch/hub/checkpoints/fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth |
| CLIP | ~/.cache/clip/ViT-B-32.pt |
各环境 vendor 挂载主机(读写)
| 环境 | SSH Host | 卷上路径(与 /opt/vendor 对应) |
|---|---|---|
| DEV | wpinfra |
/mnt/jfs-dev/shared-libraries/vendor/models/office_vlm/ |
| UAT | gpurunner |
/data/vendor/models/office_vlm/ |
| SIT | databallsitslave(或 databallsitmaster) |
/data/vendor/models/office_vlm/ |
| PROD | databallproddb |
/data/vendor/models/office_vlm/ |
说明:
- Space 容器内 vendor 只读挂载为
/opt/vendor(与上表.../vendor/为同一 JuiceFS 树)。 - SIT 边缘
databall01为/mnt/jfs-sit-vendor→ 容器/opt/vendor。 - DEV→SIT vendor 全量同步见
pms/scripts/juicefs/rsync_wpinfra_to_sit_vendor.sh;本目录随 vendor 树一并同步。
本仓库脚本
| 脚本 | 作用 |
|---|---|
setup_model_cache.sh |
幂等 ln -sf vendor → ~/.cache |
gzsim_run.sh |
启动仿真前自动 source setup_model_cache.sh |
运维上传脚本(pms 仓库):pms/scripts/vendor/upload_office_vlm_models.sh
手动下载示例
mkdir -p office_vlm_models/torch/hub/checkpoints office_vlm_models/clip
curl -fL -o office_vlm_models/torch/hub/checkpoints/fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth \
https://download.pytorch.org/models/fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth
curl -fL -o office_vlm_models/clip/ViT-B-32.pt \
https://openaipublic.azureedge.net/clip/models/40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af/ViT-B-32.pt
sha256sum office_vlm_models/clip/ViT-B-32.pt
# 应等于 40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af