From 02982a47edd6e14d3e4c2b4ab222a61d24187c60 Mon Sep 17 00:00:00 2001
From: "Brian W. Goldman" <2237679+brianwgoldman@users.noreply.github.com>
Date: Tue, 9 Jan 2024 11:29:00 -0700
Subject: [PATCH] Fix breakage caused by #2172 (#2194)

---
 src/helm/benchmark/metrics/basic_metrics.py | 11 +++++++----
 src/helm/benchmark/metrics/metric.py        |  4 +++-
 2 files changed, 10 insertions(+), 5 deletions(-)

diff --git a/src/helm/benchmark/metrics/basic_metrics.py b/src/helm/benchmark/metrics/basic_metrics.py
index 26e3b7ac5f..f4a17dc065 100644
--- a/src/helm/benchmark/metrics/basic_metrics.py
+++ b/src/helm/benchmark/metrics/basic_metrics.py
@@ -243,11 +243,14 @@ def compute_logprob_and_length(request_state: RequestState, window_service: Wind
             raise ValueError(f"Unknown adapter method: {adapter_spec.method}")
 
         stats: List[Stat] = []
-        for request_state in reference_request_states:
-            stats.extend(
-                compute_request_state_metrics(self.efficiency_metric, adapter_spec, request_state, metric_service)
-            )
 
+        general_metrics: Dict[MetricName, Stat] = {}
+        for request_state in reference_request_states:
+            for stat in compute_request_state_metrics(
+                self.efficiency_metric, adapter_spec, request_state, metric_service
+            ):
+                merge_stat(general_metrics, stat)
+        stats.extend(general_metrics.values())
         max_prob = np.max(scipy.special.softmax(reference_scores))
 
         # Multiple references may attain the same maximal score; in such cases,
diff --git a/src/helm/benchmark/metrics/metric.py b/src/helm/benchmark/metrics/metric.py
index 464c31fd8c..7d41eab707 100644
--- a/src/helm/benchmark/metrics/metric.py
+++ b/src/helm/benchmark/metrics/metric.py
@@ -288,7 +288,9 @@ def compute_worst_case_metrics(self, per_instance_stats: Dict[Instance, List[Sta
             for stat in stats:  # go through all the perturbations of the instance and merge relevant stats
                 perturbation = stat.name.perturbation
                 if perturbation is None:
-                    assert original_stat is None  # we should only have one original stat
+                    assert (
+                        original_stat is None
+                    ), f"For {metric_name} got both {original_stat} and {stat}"  # we should only have one original stat
                     original_stat = stat
                 else:
                     if perturbation.robustness: