feat(datasets) Add a check for same object partitioners (adap#4335)

Co-authored-by: jafermarq <javier@flower.ai>

datasets/flwr_datasets/federated_dataset.py

@@ -128,6 +128,7 @@ def __init__(
         self._partitioners: Dict[str, Partitioner] = _instantiate_partitioners(
             partitioners
         )
+        self._check_partitioners_correctness()
         self._shuffle = shuffle
         self._seed = seed
         #  _dataset is prepared lazily on the first call to `load_partition`
@@ -336,3 +337,20 @@ def _check_if_no_split_keyword_possible(self) -> None:
                 "Please set the `split` argument. You can only omit the split keyword "
                 "if there is exactly one partitioner specified."
             )
+
+    def _check_partitioners_correctness(self) -> None:
+        """Check if the partitioners are correctly specified.
+
+        Check if each partitioner is a different Python object. Using the same
+        partitioner for different splits is not allowed.
+        """
+        partitioners_keys = list(self._partitioners.keys())
+        for i, first_split in enumerate(partitioners_keys):
+            for j in range(i + 1, len(partitioners_keys)):
+                second_split = partitioners_keys[j]
+                if self._partitioners[first_split] is self._partitioners[second_split]:
+                    raise ValueError(
+                        f"The same partitioner object is used for multiple splits: "
+                        f"('{first_split}', '{second_split}'). "
+                        "Each partitioner should be a separate object."
+                    )

datasets/flwr_datasets/federated_dataset_test.py

@@ -32,6 +32,7 @@
     _load_mocked_dataset_dict_by_partial_download,
 )
 from flwr_datasets.partitioner import IidPartitioner, NaturalIdPartitioner, Partitioner
+from flwr_datasets.preprocessor.divider import Divider
 
 mocked_datasets = ["cifar100", "svhn", "sentiment140", "speech_commands"]
 
@@ -568,6 +569,57 @@ def test_use_load_dataset_kwargs(self) -> None:
         with self.assertRaises(ValueError):
             _ = fds.load_partition(0)
 
+    def test_incorrect_two_partitioners(self) -> None:
+        """Test if the method raises ValueError with incorrect partitioners."""
+        partitioner = IidPartitioner(num_partitions=10)
+        partitioners: dict[str, Union[Partitioner, int]] = {
+            "train": partitioner,
+            "test": partitioner,
+        }
+        first_split = "train"
+        second_split = "test"
+        with self.assertRaises(ValueError) as context:
+            FederatedDataset(
+                dataset="mnist",
+                partitioners=partitioners,
+            )
+        self.assertIn(
+            f"The same partitioner object is used for multiple splits: "
+            f"('{first_split}', '{second_split}'). "
+            "Each partitioner should be a separate object.",
+            str(context.exception),
+        )
+
+    def test_incorrect_three_partitioners(self) -> None:
+        """Test if the method raises ValueError with incorrect partitioners."""
+        partitioner = IidPartitioner(num_partitions=10)
+        partitioners: dict[str, Union[int, Partitioner]] = {
+            "train1": partitioner,
+            "train2": 10,
+            "test": partitioner,
+        }
+        divider = Divider(
+            divide_config={
+                "train1": 0.5,
+                "train2": 0.5,
+            },
+            divide_split="train",
+        )
+
+        with self.assertRaises(
+            ValueError,
+        ) as context:
+
+            FederatedDataset(
+                dataset="mnist", partitioners=partitioners, preprocessor=divider
+            )
+
+        self.assertIn(
+            "The same partitioner object is used for multiple splits: "
+            "('train1', 'test'). Each partitioner should be a separate object.",
+            str(context.exception),
+        )
+
 
 def datasets_are_equal(ds1: Dataset, ds2: Dataset) -> bool:
     """Check if two Datasets have the same values."""