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Download DD_ASSET_COMPLETENESS_CHECKLIST.md from Passenger555/DatasetDistillationCollection: direct link, hf CLI and curl.
- Browser
- Download file 4.95 kB
-
https://huggingface.co/datasets/Passenger555/DatasetDistillationCollection/resolve/main/DD_ASSET_COMPLETENESS_CHECKLIST.md
- Command line
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hf download hf://datasets/Passenger555/DatasetDistillationCollection/DD_ASSET_COMPLETENESS_CHECKLIST.md
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curl -L -o DD_ASSET_COMPLETENESS_CHECKLIST.md https://huggingface.co/datasets/Passenger555/DatasetDistillationCollection/resolve/main/DD_ASSET_COMPLETENESS_CHECKLIST.md
4.95 kB
DD 资产完整性清单
synthetic_imagefolders.tar.gzother_pretrained_models.tar
结论
synthetic_imagefolders.tar.gz:13 个 DD 方法的内层压缩包都存在且均可完整读取,但方法 × 数据集 × IPC 覆盖不全。other_pretrained_models.tar:归档可读取,但没有包含当前 ResNet-based 配置所引用的全部 teacher checkpoint。- 因此,仅依靠这两个归档不能完整运行当前项目的全部实验组合。
1. synthetic_imagefolders.tar.gz
1.1 内层方法包
- DC
- DM
- DSA
- ATT
- MTT
- TESLA
- FreD
- NCFM
- CVDD
- G-VBSM(归档目录名为
GVBSM) - SCDD
- SRe²L(归档目录名为
SRe2L) - WMDD
1.2 数据集与 IPC 覆盖
单元格中的数字表示归档内实际存在的 IPC;— 表示没有该数据集。
| 家族 | 方法 | CIFAR-10 | CIFAR-100 | TinyImageNet200 | ImageNette | ImageNet-1K |
|---|---|---|---|---|---|---|
| ConvNet-based | DC | 1/10/50 | 1/10/50 | — | — | — |
| ConvNet-based | DM | 1/10/50 | 1/10/50 | — | — | — |
| ConvNet-based | DSA | 1/10/50 | 1/10/50 | — | — | — |
| ConvNet-based | ATT | 1/10/50 | 1/10/50 | 1/10/50 | 1/10 | — |
| ConvNet-based | MTT | 1/10/50 | 1/10/50 | 1/10/50 | 1/10 | — |
| ConvNet-based | TESLA | 1/10/50 | 1/10/50 | 1/10/50 | 1/10 | — |
| ConvNet-based | FreD | 1/10/50 | 1/10/50 | 1 | 1/10 | — |
| ConvNet-based | NCFM | 1/10/50 | 1/10/50 | 1/10/50 | 1/10/50 | — |
| ResNet-based | CVDD | 1/10/50 | 1/10/50 | 1/10/50 | 1/10/50 | 1/10/50 |
| ResNet-based | G-VBSM | 1/10/50 | 1/10/50 | 1/10/50 | — | 1/10/50 |
| ResNet-based | SCDD | 1/10/50 | 1/10/50 | — | — | — |
| ResNet-based | SRe²L | — | — | 1/10/50 | — | 1/10/50 |
| ResNet-based | WMDD | — | — | 1/10/50 | 10/50 | 1/10/50 |
2. other_pretrained_models.tar
2.1 当前 ResNet-based 配置的精确路径核对
| 使用方 | 数据集 | 当前配置引用 | 归档状态 |
|---|---|---|---|
| CVDD | CIFAR-10 | other_pretrained_models/CVDD/cifar10/ResNet18.pth |
[x] 在 |
| CVDD | CIFAR-100 | other_pretrained_models/CVDD/cifar100/ResNet18.pth |
[x] 在 |
| CVDD | TinyImageNet200 | other_pretrained_models/GVBSM/tiny/ResNet18/squeeze_ResNet18.pth |
[ ] 缺失 |
| CVDD | ImageNet-1K | offcial_resnet18(运行时 torchvision 权重) |
[ ] 归档中无文件 |
| G-VBSM | CIFAR-10 | other_pretrained_models/GVBSM/CIFAR-10/ResNet18/squeeze_ResNet18.pth |
[x] 在 |
| G-VBSM | CIFAR-100 | other_pretrained_models/GVBSM/CIFAR-100/ResNet18/squeeze_ResNet18.pth |
[x] 在 |
| G-VBSM | TinyImageNet200 | other_pretrained_models/GVBSM/tiny/ResNet18/squeeze_ResNet18.pth |
[ ] 缺失 |
| G-VBSM | ImageNet-1K | offcial_resnet18(运行时 torchvision 权重) |
[ ] 归档中无文件 |
| SCDD | CIFAR-10 | other_pretrained_models/SRe2L/cifar10/ckpt.pth |
[ ] 缺失 |
| SCDD | CIFAR-100 | other_pretrained_models/SRe2L/cifar100/ckpt.pth |
[ ] 缺失 |
| SCDD | ImageNet-1K | offcial_resnet18(运行时 torchvision 权重) |
[ ] 归档中无文件 |
| SRe²L | CIFAR-10 | other_pretrained_models/SRe2L/cifar10/ckpt.pth |
[ ] 缺失 |
| SRe²L | CIFAR-100 | other_pretrained_models/SRe2L/cifar100/ckpt.pth |
[ ] 缺失 |
| SRe²L | ImageNet-1K | offcial_resnet18(运行时 torchvision 权重) |
[ ] 归档中无文件 |
| WMDD | CIFAR-10 | other_pretrained_models/SRe2L/cifar10/ckpt.pth |
[ ] 缺失 |
| WMDD | CIFAR-100 | other_pretrained_models/SRe2L/cifar100/ckpt.pth |
[ ] 缺失 |
| WMDD | TinyImageNet200 | other_pretrained_models/WMDD/tiny-imagenet_model_49.pth |
[x] 在 |
| WMDD | ImageNet-1K | offcial_resnet18(运行时 torchvision 权重) |
[ ] 归档中无文件 |
补充:
-
other_pretrained_models/WMDD/imagenette_model_49.pth存在,可对应 WMDD 的 ImageNette reproduction 配置。 offcial_resnet18是项目代码中的既有拼写;它不是归档路径,而是触发 torchvision 加载 ImageNet 预训练 ResNet-18。
2.2 唯一的关键缺失 checkpoint
以下 3 个唯一文件缺失,共影响当前 8 个 ResNet-based 配置:
-
other_pretrained_models/GVBSM/tiny/ResNet18/squeeze_ResNet18.pth -
other_pretrained_models/SRe2L/cifar10/ckpt.pth -
other_pretrained_models/SRe2L/cifar100/ckpt.pth
另外,ImageNet-1K 的 official ResNet-18 权重不在该归档中:
- torchvision official ResNet-18 checkpoint
2.3 数量汇总
以当前 tools/configs/tricks/ 中 18 个 ResNet-based 方法配置为口径:
- 5 个配置的精确本地 teacher 路径能在归档中找到。
- 8 个配置引用了归档中缺失的本地 teacher 文件。
- 5 个 ImageNet-1K 配置依赖归档外的 torchvision official ResNet-18。
归档中标记为存在的关键 teacher 文件均为非空文件,并已完整读取其载荷;文件长度与 tar 元数据一致。