mark metricmodule methods as experimental

Summary: tsia

Reviewed By: kausv

Differential Revision: D75014609

Author: iamzainhuda

torchrec/metrics/metric_module.py

@@ -68,6 +68,7 @@
 from torchrec.metrics.unweighted_ne import UnweightedNEMetric
 from torchrec.metrics.weighted_avg import WeightedAvgMetric
 from torchrec.metrics.xauc import XAUCMetric
+from torchrec.utils.experimental import experimental
 
 
 logger: logging.Logger = logging.getLogger(__name__)
@@ -395,6 +396,7 @@ def _get_metric_states(
 
         return state_aggregated
 
+    @experimental
     def get_pre_compute_states(
         self, pg: Union[dist.ProcessGroup, DeviceMesh], reduce_metrics: bool = True
     ) -> Dict[str, Dict[str, Dict[str, torch.Tensor]]]:
@@ -438,6 +440,7 @@ def get_pre_compute_states(
 
         return aggregated_states
 
+    @experimental
     def load_pre_compute_states(
         self, source: Dict[str, Dict[str, Dict[str, torch.Tensor]]]
     ) -> None: