Repository: IBM/unitxt

Issue:
Remove dependency on Transformers and Torch when loading a dataset
Consider this code:

```python
from unitxt import load_dataset

load_dataset('card=cards.rag.benchmark.miniwiki.en,template_card_index=default')
```

When running it, Python reports a "module not found" error that `Transformers` and `Torch` are not installed.

This is probably because Unitxt attempts to import or even load the metrics associated with the task that the dataset is assigned to.

As discussed with @elronbandel and @yoavkatz - the metrics shouldn't be imported / loaded when the user just wants to load a dataset.

Discussion:

Solution patch:
diff --git a/src/unitxt/task.py b/src/unitxt/task.py
index e9140cb7..5ce5f71d 100644
--- a/src/unitxt/task.py
+++ b/src/unitxt/task.py
@@ -1,14 +1,14 @@
 import warnings
-from functools import lru_cache
 from typing import Any, Dict, List, Optional, Union
 
+from .artifact import fetch_artifact
 from .deprecation_utils import deprecation
 from .error_utils import Documentation, UnitxtError, UnitxtWarning
 from .logging_utils import get_logger
 from .metrics import MetricsList
 from .operator import InstanceOperator
 from .operators import ArtifactFetcherMixin
-from .settings_utils import get_constants
+from .settings_utils import get_constants, get_settings
 from .templates import Template
 from .type_utils import (
     Type,
@@ -25,6 +25,7 @@ from .type_utils import (
 
 constants = get_constants()
 logger = get_logger()
+settings = get_settings()
 
 
 @deprecation(
@@ -213,9 +214,9 @@ class Task(InstanceOperator, ArtifactFetcherMixin):
         return data
 
     @classmethod
-    @lru_cache(maxsize=None)
-    def get_metrics_artifacts(cls, metric_id: str):
-        metric = cls.get_artifact(metric_id)
+    def get_metrics_artifact_without_load(cls, metric_id: str):
+        with settings.context(skip_artifacts_prepare_and_verify=True):
+            metric, _ = fetch_artifact(metric_id)
         if isinstance(metric, MetricsList):
             return metric.items
         return [metric]
@@ -223,7 +224,7 @@ class Task(InstanceOperator, ArtifactFetcherMixin):
     def check_metrics_type(self) -> None:
         prediction_type = self.prediction_type
         for metric_id in self.metrics:
-            metric_artifacts_list = Task.get_metrics_artifacts(metric_id)
+            metric_artifacts_list = Task.get_metrics_artifact_without_load(metric_id)
             for metric_artifact in metric_artifacts_list:
                 metric_prediction_type = metric_artifact.prediction_type
                 if (


Test patch:
diff --git a/tests/library/test_artifact.py b/tests/library/test_artifact.py
index ea7fabec..af8fa291 100644
--- a/tests/library/test_artifact.py
+++ b/tests/library/test_artifact.py
@@ -430,12 +430,12 @@ class TestArtifact(UnitxtTestCase):
             actual_metrics_of_task_as_is = []
             for metric_id in task_as_is.metrics:
                 actual_metrics_of_task_as_is.extend(
-                    Task.get_metrics_artifacts(metric_id)
+                    Task.get_metrics_artifact_without_load(metric_id)
                 )
             actual_metrics_of_task_indirect = []
             for metric_id in task_indirect.metrics:
                 actual_metrics_of_task_indirect.extend(
-                    Task.get_metrics_artifacts(metric_id)
+                    Task.get_metrics_artifact_without_load(metric_id)
                 )
 
             actual_metrics_to_dict_of_task_as_is = [