fix: fixed devices with new polars implementation (#756)

### Summary of Changes

fix: fixed devices with new polars implementation
refactor: using `_utils._get_random_seed` in `ImageList.from_files` to
shuffle all files

---------

Co-authored-by: megalinter-bot <129584137+megalinter-bot@users.noreply.github.com>

Author: Marsmaennchen221

src/safeds/data/image/containers/_image_list.py

@@ -10,6 +10,7 @@
 from typing import TYPE_CHECKING, Literal, overload
 
 from safeds._config import _init_default_device
+from safeds._utils import _get_random_seed
 from safeds.data.image.containers._image import Image
 from safeds.exceptions import OutOfBoundsError, ClosedBound
 
@@ -176,6 +177,8 @@ def from_files(
 
         _init_default_device()
 
+        random.seed(_get_random_seed())
+
         from safeds.data.image.containers._empty_image_list import _EmptyImageList
         from safeds.data.image.containers._multi_size_image_list import _MultiSizeImageList
         from safeds.data.image.containers._single_size_image_list import _SingleSizeImageList

src/safeds/data/labeled/containers/_image_dataset.py

@@ -5,7 +5,7 @@
 import warnings
 from typing import TYPE_CHECKING, Generic, TypeVar
 
-from safeds._config import _init_default_device
+from safeds._config import _get_device, _init_default_device
 from safeds._utils import _structural_hash
 from safeds.data.image.containers import ImageList
 from safeds.data.image.containers._empty_image_list import _EmptyImageList
@@ -294,7 +294,7 @@ def __init__(self, table: Table) -> None:
         _init_default_device()
 
         self._column_names = table.column_names
-        self._tensor = torch.Tensor(table._data_frame.to_numpy()).to(torch.get_default_device())
+        self._tensor = torch.Tensor(table._data_frame.to_torch()).to(_get_device())
 
         if not torch.all(self._tensor.sum(dim=1) == torch.ones(self._tensor.size(dim=0))):
             raise ValueError(
@@ -355,8 +355,8 @@ def __init__(self, column: Column) -> None:
                 category=UserWarning,
             )
             self._one_hot_encoder = OneHotEncoder().fit(column_as_table, [self._column_name])
-        self._tensor = torch.Tensor(self._one_hot_encoder.transform(column_as_table)._data_frame.to_numpy()).to(
-            torch.get_default_device(),
+        self._tensor = torch.Tensor(self._one_hot_encoder.transform(column_as_table)._data_frame.to_torch()).to(
+            _get_device(),
         )
 
     def __eq__(self, other: object) -> bool:

src/safeds/data/labeled/containers/_time_series_dataset.py

@@ -3,7 +3,7 @@
 import sys
 from typing import TYPE_CHECKING, Any
 
-from safeds._config import _init_default_device
+from safeds._config import _get_device, _init_default_device
 from safeds._utils import _structural_hash
 from safeds.exceptions import ClosedBound, OutOfBoundsError
 
@@ -235,7 +235,7 @@ def _into_dataloader_with_window(self, window_size: int, forecast_horizon: int,
             label = target_tensor[i + window_size + forecast_horizon]
             for col in feature_cols:
                 data = torch.tensor(col._series.to_numpy(), dtype=torch.float32)
-                window = torch.cat((window, data[i: i + window_size]), dim=0)
+                window = torch.cat((window, data[i : i + window_size]), dim=0)
             x_s.append(window)
             y_s.append(label)
         x_s_tensor = torch.stack(x_s)
@@ -279,7 +279,7 @@ def _into_dataloader_with_window_predict(
 
         _init_default_device()
 
-        target_tensor = self.target._series.to_torch()
+        target_tensor = self.target._series.to_torch().to(_get_device())
         x_s = []
 
         size = target_tensor.size(0)

src/safeds/data/tabular/containers/_table.py

@@ -1994,7 +1994,7 @@ def _into_dataloader(self, batch_size: int) -> DataLoader:
         _init_default_device()
 
         return DataLoader(
-            dataset=_create_dataset(self._data_frame.to_torch(dtype=pl.Float32)),
+            dataset=_create_dataset(self._data_frame.to_torch(dtype=pl.Float32).to(_get_device())),
             batch_size=batch_size,
             generator=torch.Generator(device=_get_device()),
         )

tests/safeds/data/image/containers/__snapshots__/test_image_list/TestFromFiles.test_from_files_creation_load_percentage[all-images-cpu].png

@@ -38,22 +38,22 @@ class TestImageToTableClassifier:
             (
                 1234,
                 device_cuda,
-                ["grayscale"] * 7,
+                ["white_square"] * 7,
             ),
             (
                 4711,
                 device_cuda,
-                ["white_square"] * 7,
+                ["rgba"] * 7,
             ),
             (
                 1234,
                 device_cpu,
-                ["grayscale"] * 7,
+                ["white_square"] * 7,
             ),
             (
                 4711,
                 device_cpu,
-                ["white_square"] * 7,
+                ["rgba"] * 7,
             ),
         ],
         ids=["seed-1234-cuda", "seed-4711-cuda", "seed-1234-cpu", "seed-4711-cpu"],
@@ -106,22 +106,22 @@ class TestImageToColumnClassifier:
             (
                 1234,
                 device_cuda,
-                ["grayscale"] * 7,
+                ["white_square"] * 7,
             ),
             (
                 4711,
                 device_cuda,
-                ["white_square"] * 7,
+                ["rgba"] * 7,
             ),
             (
                 1234,
                 device_cpu,
-                ["grayscale"] * 7,
+                ["white_square"] * 7,
             ),
             (
                 4711,
                 device_cpu,
-                ["white_square"] * 7,
+                ["rgba"] * 7,
             ),
         ],
         ids=["seed-1234-cuda", "seed-4711-cuda", "seed-1234-cpu", "seed-4711-cpu"],