Upload eval_utils.py with huggingface_hub

eval_utils.py

@@ -31,13 +31,13 @@ def _(
             metric = verbosed_fetch_artifact(metric_name)
             metric_step = as_remote_metric(metric)
         else:
-            # The SequentialOperator below will handle the load of the metric fromm its name
+            # The SequentialOperator below will handle the load of the metric from its name
             metric_step = metric_name
         metrics_operator = SequentialOperator(steps=[metric_step])
 
         if not compute_conf_intervals:
             first_step = metrics_operator.steps[0]
-            n_resamples = first_step.disable_confidence_interval_calculation()
+            first_step.disable_confidence_interval_calculation()
 
         instances = list(metrics_operator(multi_stream)["test"])
         for entry, instance in zip(dataset, instances):
@@ -46,13 +46,6 @@ def _(
         if len(instances) > 0:
             global_scores[metric_name] = instances[0]["score"].get("global", {})
 
-        # To overcome issue #325: the modified metric artifact is cached and
-        # a sequential retrieval of an artifact with the same name will
-        # retrieve the metric with the previous modification.
-        # This reverts the confidence interval change and restores the initial metric.
-        if not compute_conf_intervals:
-            first_step.set_n_resamples(n_resamples)
-
     return dataset, global_scores