Guard optional rapidata metric import and tighten validation

Author: cursoragent

src/pruna/evaluation/metrics/__init__.py

@@ -22,10 +22,15 @@
 from pruna.evaluation.metrics.metric_memory import DiskMemoryMetric, InferenceMemoryMetric, TrainingMemoryMetric
 from pruna.evaluation.metrics.metric_model_architecture import TotalMACsMetric, TotalParamsMetric
 from pruna.evaluation.metrics.metric_pairwise_clip import PairwiseClipScore
-from pruna.evaluation.metrics.metric_rapiddata import RapidataMetric
 from pruna.evaluation.metrics.metric_sharpness import SharpnessMetric
 from pruna.evaluation.metrics.metric_torch import TorchMetricWrapper
 
+try:
+    from pruna.evaluation.metrics.metric_rapiddata import RapidataMetric
+except ModuleNotFoundError as e:
+    if e.name != "rapidata":
+        raise
+
 __all__ = [
     "MetricRegistry",
     "TorchMetricWrapper",
@@ -44,5 +49,7 @@
     "DinoScore",
     "SharpnessMetric",
     "AestheticLAION",
-    "RapidataMetric",
 ]
+
+if "RapidataMetric" in globals():
+    __all__.append("RapidataMetric")

src/pruna/evaluation/metrics/metric_rapiddata.py

@@ -299,6 +299,7 @@ def compute(self) -> None:
         :meth:`retrieve_granular_results` once enough votes have been
         collected.
         """
+        self._require_benchmark()
         self._require_model()
         if not self.media_cache:
             raise ValueError("No data accumulated. Call update() before compute().")
@@ -348,7 +349,7 @@ def retrieve_results(self, *args, **kwargs) -> CompositeMetricResult | None:
             if "ValidationError" in type(e).__name__:
                 pruna_logger.warning(
                     "The benchmark hasn't finished yet.\n "
-                    "Please wait for more votes and try again."
+                    "Please wait for more votes and try again.\n "
                     "Skipping."
                 )
                 return None