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fix initialization of Accuracy to work with new version of torchmetrics #4

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fix initialization of Accuracy to work with new version of torchmetrics #4

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7 changes: 4 additions & 3 deletions hydra_lightning/tasks/example/modules/base_adv.py
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Expand Up @@ -15,9 +15,10 @@ class BaseAdvModule(BaseModule):
def initialize_model(self):
self.cross_entropy_criterion = torch.nn.CrossEntropyLoss()

self.train_accuracy = Accuracy()
self.std_val_accuracy = Accuracy()
self.adv_val_accuracy = Accuracy()
cfg: DictConfig = self.hparams.model_config
self.train_accuracy = Accuracy(task='multiclass', num_classes=cfg.num_classes)
self.std_val_accuracy = Accuracy(task='multiclass', num_classes=cfg.num_classes)
self.adv_val_accuracy = Accuracy(task='multiclass', num_classes=cfg.num_classes)

# for robby.input_transforms.PGD
@staticmethod
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4 changes: 2 additions & 2 deletions hydra_lightning/tasks/example/modules/resnet_robust_train.py
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Expand Up @@ -14,9 +14,9 @@ class ResnetRobustTrainModule(BaseAdvModule):
def initialize_model(self):
super().initialize_model()

self.adv_train_accuracy = Accuracy()

cfg: DictConfig = self.hparams.model_config
self.adv_train_accuracy = Accuracy(task='multiclass', num_classes=cfg.num_classes)

self.backbone, num_features = get_robust_backbone(cfg.arch, cfg.eps)
self.head = nn.Linear(num_features, cfg.num_classes)

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