Add get_config to BruteForceRetrieval layer.

For consistency with other layers. Note that this does not serialize candidates.

keras_rs/src/layers/retrieval/brute_force_retrieval.py

@@ -22,6 +22,10 @@ class BruteForceRetrieval(keras.layers.Layer):
     The identifiers for the candidates can be specified as a tensor. If not
     provided, the IDs used are simply the candidate indices.
 
+    Note that the serialization of this layer does not preserve the candidates
+    and only saves the `k` and `return_scores` arguments. One has to call
+    `update_candidates` after deserializing the layers.
+
     Args:
         candidate_embeddings: The candidate embeddings. If `None`,
             candidates must be provided using `update_candidates` before
@@ -183,3 +187,13 @@ def compute_score(
         return keras.ops.matmul(
             query_embedding, keras.ops.transpose(candidate_embedding)
         )
+
+    def get_config(self) -> dict[str, Any]:
+        config: dict[str, Any] = super().get_config()
+        config.update(
+            {
+                "k": self.k,
+                "return_scores": self.compute_score,
+            }
+        )
+        return config