fix: use to_torch instead of to_numpy

This properly creates writeable numpy arrays.
Safe-DS · May 29, 2024 · 578cb9d · 578cb9d
1 parent 82322a9
commit 578cb9d
Showing 1 changed file with 4 additions and 4 deletions.
diff --git a/src/safeds/data/labeled/containers/_tabular_dataset.py b/src/safeds/data/labeled/containers/_tabular_dataset.py
@@ -196,8 +196,8 @@ def _into_dataloader_with_classes(self, batch_size: int, num_of_classes: int) ->
         if num_of_classes <= 2:
             return DataLoader(
                 dataset=_create_dataset(
-                    torch.Tensor(self.features._data_frame.to_numpy()).to(_get_device()),
-                    torch.Tensor(self.target._series.to_numpy()).to(_get_device()).unsqueeze(dim=-1),
+                    self.features._data_frame.to_torch().to(_get_device()),
+                    self.target._series.to_torch().to(_get_device()).unsqueeze(dim=-1),
                 ),
                 batch_size=batch_size,
                 shuffle=True,
@@ -206,9 +206,9 @@ def _into_dataloader_with_classes(self, batch_size: int, num_of_classes: int) ->
         else:
             return DataLoader(
                 dataset=_create_dataset(
-                    torch.Tensor(self.features._data_frame.to_numpy()).to(_get_device()),
+                    self.features._data_frame.to_torch().to(_get_device()),
                     torch.nn.functional.one_hot(
-                        torch.LongTensor(self.target._series.to_numpy()).to(_get_device()),
+                        self.target._series.to_torch().to(_get_device()),
                         num_classes=num_of_classes,
                     ),
                 ),