(dataset, batch_size, root='./data', train=True)
| 106 | |
| 107 | |
| 108 | def get_indexed_loader(dataset, batch_size, root='./data', train=True): |
| 109 | if dataset == 'imagenet' or dataset == 'imagenet-mini': |
| 110 | return imagenet_utils.get_indexed_loader(dataset, batch_size, root, train) |
| 111 | |
| 112 | target_set = get_dataset(dataset, root=root, train=train) |
| 113 | |
| 114 | if train: |
| 115 | target_set = data.IndexedDataset(x=target_set.x, y=target_set.y, transform=target_set.transform) |
| 116 | else: |
| 117 | target_set = data.Dataset(x=target_set.x, y=target_set.y, transform=target_set.transform) |
| 118 | |
| 119 | if train: |
| 120 | loader = data.Loader(target_set, batch_size=batch_size, shuffle=True, drop_last=True) |
| 121 | else: |
| 122 | loader = data.Loader(target_set, batch_size=batch_size, shuffle=False, drop_last=False) |
| 123 | |
| 124 | return loader |
| 125 | |
| 126 | |
| 127 | def get_indexed_tensor_loader(dataset, batch_size, root='./data', train=True): |
nothing calls this directly
no test coverage detected