Fix splits with overfit batches

CHANGELOG.md

@@ -10,10 +10,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Added `deeplabv3`, `lraspp`, and `unet` backbones for the `SemanticSegmentation` task ([#370](https://github.com/PyTorchLightning/lightning-flash/pull/370))
 
-### Fixed
-
-- Fixed `flash.Trainer.add_argparse_args` not adding any arguments ([#343](https://github.com/PyTorchLightning/lightning-flash/pull/343))
-
 ### Changed
 
 - Changed the installation command for extra features ([#346](https://github.com/PyTorchLightning/lightning-flash/pull/346))
@@ -26,6 +22,11 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Deprecated `SemanticSegmentation` backbone names `torchvision/fcn_resnet50` and `torchvision/fcn_resnet101`, use `fc_resnet50` and `fcn_resnet101` instead ([#370](https://github.com/PyTorchLightning/lightning-flash/pull/370))
 
+### Fixed
+
+- Fixed `flash.Trainer.add_argparse_args` not adding any arguments ([#343](https://github.com/PyTorchLightning/lightning-flash/pull/343))
+- Fixed a bug where using `val_split` with `overfit_batches` would give an infinite recursion ([#375](https://github.com/PyTorchLightning/lightning-flash/pull/375))
+
 
 ## [0.3.0] - 2021-05-20
 

flash/core/data/splits.py

@@ -13,7 +13,7 @@ class SplitDataset(Dataset):
 
         dataset: A dataset to be splitted
         indices: List of indices to expose from the dataset
-        use_duplicated_indices: Wether to allow duplicated indices.
+        use_duplicated_indices: Whether to allow duplicated indices.
 
     Example::
 
@@ -41,9 +41,9 @@ def __init__(self, dataset: Any, indices: List[int] = [], use_duplicated_indices
         self.indices = indices
 
     def __getattr__(self, key: str):
-        if key in self._INTERNAL_KEYS:
-            return getattr(self, key)
-        return getattr(self.dataset, key)
+        if key not in self._INTERNAL_KEYS:
+            return self.dataset.__getattribute__(key)
+        raise AttributeError
 
     def __setattr__(self, name: str, value: Any) -> None:
         if name in self._INTERNAL_KEYS:

tests/core/data/test_split_dataset.py → tests/core/data/test_splits.py

@@ -11,6 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from copy import deepcopy
+
 import numpy as np
 import pytest
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
@@ -19,25 +21,12 @@
 from flash.core.data.splits import SplitDataset
 
 
-def test_split_dataset(tmpdir):
-
+def test_split_dataset():
     train_ds, val_ds = DataModule._split_train_val(range(100), val_split=0.1)
     assert len(train_ds) == 90
     assert len(val_ds) == 10
     assert len(np.unique(train_ds.indices)) == len(train_ds.indices)
 
-    with pytest.raises(MisconfigurationException, match="[0, 99]"):
-        SplitDataset(range(100), indices=[100])
-
-    with pytest.raises(MisconfigurationException, match="[0, 49]"):
-        SplitDataset(range(50), indices=[-1])
-
-    with pytest.raises(MisconfigurationException, match="[0, 49]"):
-        SplitDataset(list(range(50)) + list(range(50)), indices=[-1])
-
-    with pytest.raises(MisconfigurationException, match="[0, 99]"):
-        SplitDataset(list(range(50)) + list(range(50)), indices=[-1], use_duplicated_indices=True)
-
     class Dataset:
 
         def __init__(self):
@@ -57,3 +46,27 @@ def __len__(self):
 
     split_dataset.is_passed_down = True
     assert split_dataset.dataset.is_passed_down
+
+
+def test_misconfiguration():
+    with pytest.raises(MisconfigurationException, match="[0, 99]"):
+        SplitDataset(range(100), indices=[100])
+
+    with pytest.raises(MisconfigurationException, match="[0, 49]"):
+        SplitDataset(range(50), indices=[-1])
+
+    with pytest.raises(MisconfigurationException, match="[0, 49]"):
+        SplitDataset(list(range(50)) + list(range(50)), indices=[-1])
+
+    with pytest.raises(MisconfigurationException, match="[0, 99]"):
+        SplitDataset(list(range(50)) + list(range(50)), indices=[-1], use_duplicated_indices=True)
+
+    with pytest.raises(MisconfigurationException, match="indices should be a list"):
+        SplitDataset(list(range(100)), indices="not a list")
+
+
+def test_deepcopy():
+    """Tests that deepcopy works with the ``SplitDataset``."""
+    dataset = list(range(100))
+    train_ds, val_ds = DataModule._split_train_val(dataset, val_split=0.1)
+    deepcopy(train_ds)