fixed acc_mutula_info calc position

lm_eval/api/task.py

@@ -500,10 +500,7 @@ class ConfigurableTask(Task):
 
         _metric_list = DEFAULT_METRIC_REGISTRY[self._config.output_type]
         if self._config.metric_list is None:
-            eval_logger.warning(
-                f"Output Type set as {self._config.output_type} and metric_list is not set"
-                "Will default to exact_match"
-            )
+
             for metric_name in _metric_list:
                 self._metric_fn_list[metric_name] = METRIC_REGISTRY[metric_name]
                 self._aggregation_list[metric_name] = DEFAULT_AGGREGATION_REGISTRY[
@@ -799,6 +796,16 @@ class ConfigurableTask(Task):
                     self._config.template_aliases + "{{answer_choices}}", doc
                 )
             )
+            if (
+                2 * len(choices) == len(lls)
+                and "acc_mutual_info" in self._metric_list.keys()
+            ):
+                # then we are doing mutual info.
+                # this stores the "dryrun" / unconditional answer loglikelihoods
+                lls_unconditional = lls[1::2]
+                assert len(lls_unconditional) == len(choices)
+                # and this stores our "regular" conditional loglikelihoods
+                lls = lls[::2]
 
             acc = 1.0 if np.argmax(lls) == gold else 0.0
             completion_len = np.array([float(len(i)) for i in choices])
@@ -817,14 +824,6 @@ class ConfigurableTask(Task):
                 result_dict["exact_match"] = int(is_greedy)
 
             if "acc_mutual_info" in use_metric:
-                if 2 * len(choices) == len(lls):
-                    # then we are doing mutual info.
-                    # this stores the "dryrun" / unconditional answer loglikelihoods
-                    lls_unconditional = lls[1::2]
-                    assert len(lls_unconditional) == len(choices)
-                    # and this stores our "regular" conditional loglikelihoods
-                    lls = lls[::2]
-
                 lls_mutual_info = [
                     ll_c - ll_u for ll_c, ll_u in zip(lls, lls_unconditional)
                 ]