diff --git a/datasets/flwr_datasets/partitioner/partitioner.py b/datasets/flwr_datasets/partitioner/partitioner.py
index 24ca22bbebc..0404a11e772 100644
--- a/datasets/flwr_datasets/partitioner/partitioner.py
+++ b/datasets/flwr_datasets/partitioner/partitioner.py
@@ -50,6 +50,11 @@ def dataset(self, value: Dataset) -> None:
                 "created partitions (in case the partitioning scheme needs to create "
                 "the full partitioning also in order to return a single partition)."
             )
+        if not isinstance(value, Dataset):
+            raise TypeError(
+                f"The dataset object you want to assign to the partitioner should be "
+                f"of type `datasets.Dataset` but given {type(value)}."
+            )
         self._dataset = value
 
     @abstractmethod
diff --git a/datasets/flwr_datasets/partitioner/partitioner_test.py b/datasets/flwr_datasets/partitioner/partitioner_test.py
new file mode 100644
index 00000000000..be0c988e6a9
--- /dev/null
+++ b/datasets/flwr_datasets/partitioner/partitioner_test.py
@@ -0,0 +1,59 @@
+# Copyright 2024 Flower Labs GmbH. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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.
+# ==============================================================================
+"""Abstract partitioner tests."""
+
+
+import unittest
+
+import datasets
+from datasets import Dataset
+from flwr_datasets.partitioner.partitioner import Partitioner
+
+
+class DummyPartitioner(Partitioner):
+    """Dummy partitioner for testing."""
+
+    def load_partition(self, partition_id: int) -> Dataset:
+        """Return always a dummy dataset."""
+        return datasets.Dataset.from_dict({"feature": [0, 1, 2]})
+
+    @property
+    def num_partitions(self) -> int:
+        """Return always 0."""
+        return 0
+
+
+class TestPartitioner(unittest.TestCase):
+    """Test Partitioner."""
+
+    def test_dataset_setter_incorrect_type(self) -> None:
+        """Test if the incorrect type of the dataset to dataset.setter method raises."""
+        train_split = datasets.Dataset.from_dict({"feature": [0, 1, 2]})
+        test_split = datasets.Dataset.from_dict({"feature": [0, 1, 2]})
+        dataset = datasets.DatasetDict({"train": train_split, "test": test_split})
+        partitioner = DummyPartitioner()
+
+        with self.assertRaises(Exception) as context:
+            partitioner.dataset = dataset
+        self.assertIn(
+            "The dataset object you want to assign to the partitioner should be of "
+            "type `datasets.Dataset` but given "
+            "<class 'datasets.dataset_dict.DatasetDict'>.",
+            str(context.exception),
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()