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metric.py

@@ -42,7 +42,7 @@ from .processors import __file__ as _
 from .random_utils import __file__ as _
 from .recipe import __file__ as _
 from .register import __file__ as _
-from .register import register_all_artifacts
+from .register import _reset_env_local_catalogs, register_all_artifacts
 from .renderers import __file__ as _
 from .schema import __file__ as _
 from .split_utils import __file__ as _
@@ -124,6 +124,8 @@ UNITXT_METRIC_SCHEMA = Features({"predictions": Value("string"), "references": d
 
 
 def _compute(predictions: List[str], references: Iterable, flatten: bool = False, split_name: str = "all"):
+    _reset_env_local_catalogs()
+    register_all_artifacts()
     recipe = MetricRecipe()
 
     multi_stream = recipe(predictions=predictions, references=references, split_name=split_name)
@@ -154,4 +156,20 @@ class Metric(evaluate.Metric):
         )
 
     def _compute(self, predictions: List[str], references: Iterable, flatten: bool = False, split_name: str = "all"):
-        return _compute(predictions=predictions, references=references, flatten=flatten, split_name=split_name)
+        try:
+            from unitxt.dataset import (
+                get_dataset_artifact as get_dataset_artifact_installed,
+            )
+
+            unitxt_installed = True
+        except ImportError:
+            unitxt_installed = False
+
+        if unitxt_installed:
+            from unitxt.metric import _compute as _compute_installed
+
+            return _compute_installed(
+                predictions=predictions, references=references, flatten=flatten, split_name=split_name
+            )
+        else:
+            return _compute(predictions=predictions, references=references, flatten=flatten, split_name=split_name)