Debug Datasets¶
DummyDataset¶
- class pl_bolts.datasets.dummy_dataset.DummyDataset(*shapes, num_samples=10000)[source]
Bases:
torch.utils.data.
Generate a dummy dataset.
Example
>>> from pl_bolts.datasets import DummyDataset >>> from torch.utils.data import DataLoader >>> # mnist dims >>> ds = DummyDataset((1, 28, 28), (1, )) >>> dl = DataLoader(ds, batch_size=7) >>> # get first batch >>> batch = next(iter(dl)) >>> x, y = batch >>> x.size() torch.Size([7, 1, 28, 28]) >>> y.size() torch.Size([7, 1])
DummyDetectionDataset¶
- class pl_bolts.datasets.dummy_dataset.DummyDetectionDataset(img_shape=(3, 256, 256), num_boxes=1, num_classes=2, num_samples=10000)[source]
Bases:
torch.utils.data.
Generate a dummy dataset for detection.
Example
>>> from pl_bolts.datasets import DummyDetectionDataset >>> from torch.utils.data import DataLoader >>> ds = DummyDetectionDataset() >>> dl = DataLoader(ds, batch_size=7)
RandomDataset¶
- class pl_bolts.datasets.dummy_dataset.RandomDataset(size, num_samples=250)[source]
Bases:
torch.utils.data.
Generate a dummy dataset.
Example
>>> from pl_bolts.datasets import RandomDataset >>> from torch.utils.data import DataLoader >>> ds = RandomDataset(10) >>> dl = DataLoader(ds, batch_size=7)
RandomDictDataset¶
- class pl_bolts.datasets.dummy_dataset.RandomDictDataset(size, num_samples=250)[source]
Bases:
torch.utils.data.
Generate a dummy dataset with a dict structure.
Example
>>> from pl_bolts.datasets import RandomDictDataset >>> from torch.utils.data import DataLoader >>> ds = RandomDictDataset(10) >>> dl = DataLoader(ds, batch_size=7)
RandomDictStringDataset¶
- class pl_bolts.datasets.dummy_dataset.RandomDictStringDataset(size, num_samples=250)[source]
Bases:
torch.utils.data.
Generate a dummy dataset with strings.
Example
>>> from pl_bolts.datasets import RandomDictStringDataset >>> from torch.utils.data import DataLoader >>> ds = RandomDictStringDataset(10) >>> dl = DataLoader(ds, batch_size=7)