Fix pipeline tests

src/transformers/pipelines/__init__.py

@@ -606,6 +606,7 @@ def pipeline(
 
     # Retrieve the task
     if task in custom_tasks:
+        normalized_task = task
         targeted_task, task_options = clean_custom_task(custom_tasks[task])
         if pipeline_class is None:
             if not trust_remote_code:

tests/pipelines/test_pipelines_common.py

@@ -795,7 +795,7 @@ def test_warning_logs(self):
         alias = "text-classification"
         # Get the original task, so we can restore it at the end.
         # (otherwise the subsequential tests in `TextClassificationPipelineTests` will fail)
-        original_task, original_task_options = PIPELINE_REGISTRY.check_task(alias)
+        _, original_task, _ = PIPELINE_REGISTRY.check_task(alias)
 
         try:
             with CaptureLogger(logger_) as cm:
@@ -816,7 +816,7 @@ def test_register_pipeline(self):
         )
         assert "custom-text-classification" in PIPELINE_REGISTRY.get_supported_tasks()
 
-        task_def, _ = PIPELINE_REGISTRY.check_task("custom-text-classification")
+        _, task_def, _ = PIPELINE_REGISTRY.check_task("custom-text-classification")
         self.assertEqual(task_def["pt"], (AutoModelForSequenceClassification,) if is_torch_available() else ())
         self.assertEqual(task_def["tf"], (TFAutoModelForSequenceClassification,) if is_tf_available() else ())
         self.assertEqual(task_def["type"], "text")

utils/tests_fetcher.py

@@ -377,6 +377,7 @@ def create_reverse_dependency_map():
     ],
     "optimization.py": "optimization/test_optimization.py",
     "optimization_tf.py": "optimization/test_optimization_tf.py",
+    "pipelines/__init__.py": "pipelines/test_pipelines_*.py",
     "pipelines/base.py": "pipelines/test_pipelines_*.py",
     "pipelines/text2text_generation.py": [
         "pipelines/test_pipelines_text2text_generation.py",