Add VOS model (resnet-18/imagenet200/vos/s2)

resnet-18/imagenet200/vos/s2/config.yaml

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+model:
+  _target_: pytorch_ood.model.ResNet18
+  arch_name: resnet-18
+  num_classes: 200
+  weights: null
+dataset:
+  name: imagenet200
+  kind: imagenet
+  num_classes: 200
+  root: /data/fast/scratch/imagenet-2012
+  mean:
+  - 0.485
+  - 0.456
+  - 0.406
+  std:
+  - 0.229
+  - 0.224
+  - 0.225
+  image_size: 224
+  pre_size: 256
+loss:
+  _target_: pytorch_ood.loss.VOSRegLoss
+  method_name: vos
+  alpha: 0.1
+  device: cuda:0
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0005
+  nesterov: true
+outliers:
+  name: imagenet800
+  _target_: pytorch_ood.dataset.img.ImageNet800
+  root: /data/fast/scratch/imagenet-2012
+seed: 2
+deterministic: true
+imagenet_root: /data/fast/scratch/imagenet-2012
+init_from: resnet-18/imagenet200/crossentropy/s2
+epochs: 10
+batch_size: 128
+oe_batch_size: 256
+num_workers: 8
+device: cuda:0
+scheduler:
+  _target_: scheduler.per_iteration_cosine
+  lr_min: 1.0e-06

resnet-18/imagenet200/vos/s2/metrics.json

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+{
+  "final_accuracy": 0.8389999866485596,
+  "best_accuracy": 0.843999981880188
+}

resnet-18/imagenet200/vos/s2/model-8f9642c7f6d66d39.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f9642c7f6d66d39658e36bcc898c25e55cf24dd04434fdc27860d86709ad58f
+size 45184322