(self, train, ulb)
| 146 | self.num_labels = num_labels // num_class |
| 147 | |
| 148 | def get_transform(self, train, ulb): |
| 149 | if train: |
| 150 | transform = transforms.Compose([ |
| 151 | transforms.Resize([256, 256]), |
| 152 | transforms.RandomHorizontalFlip(), |
| 153 | transforms.RandomCrop(224, padding=4, padding_mode='reflect'), |
| 154 | transforms.ToTensor(), |
| 155 | transforms.Normalize(mean["imagenet"], std["imagenet"])]) |
| 156 | else: |
| 157 | transform = transforms.Compose([ |
| 158 | transforms.Resize([224, 224]), |
| 159 | transforms.ToTensor(), |
| 160 | transforms.Normalize(mean["imagenet"], std["imagenet"])]) |
| 161 | return transform |
| 162 | |
| 163 | def get_lb_train_data(self): |
| 164 | transform = self.get_transform(train=True, ulb=False) |
no outgoing calls
no test coverage detected