From 00d0b32ea4ad11c8fd08a18c11c1952af22bac8c Mon Sep 17 00:00:00 2001
From: Ella Charlaix <ella@huggingface.co>
Date: Mon, 9 Dec 2024 18:10:59 +0100
Subject: [PATCH] fix

---
 tests/onnxruntime/test_modeling.py | 22 ++++++++++++++++++++--
 1 file changed, 20 insertions(+), 2 deletions(-)

diff --git a/tests/onnxruntime/test_modeling.py b/tests/onnxruntime/test_modeling.py
index 8f52ef45180..fe358249480 100644
--- a/tests/onnxruntime/test_modeling.py
+++ b/tests/onnxruntime/test_modeling.py
@@ -1388,10 +1388,11 @@ def test_pipeline_model_is_none(self):
         question = "Whats my name?"
         context = "My Name is Philipp and I live in Nuremberg."
         outputs = pipe(question, context)
-
         # compare model output class
         self.assertGreaterEqual(outputs["score"], 0.0)
         self.assertIsInstance(outputs["answer"], str)
+        del pipe
+        gc.collect()
 
     @parameterized.expand(
         grid_parameters(
@@ -1576,6 +1577,8 @@ def test_pipeline_model_is_none(self):
         # compare model output class
         self.assertGreaterEqual(outputs[0]["score"], 0.0)
         self.assertIsInstance(outputs[0]["token_str"], str)
+        del pipe
+        gc.collect()
 
     @parameterized.expand(SUPPORTED_ARCHITECTURES)
     @require_torch_gpu
@@ -1756,6 +1759,8 @@ def test_pipeline_model_is_none(self):
         # compare model output class
         self.assertGreaterEqual(outputs[0]["score"], 0.0)
         self.assertIsInstance(outputs[0]["label"], str)
+        del pipe
+        gc.collect()
 
     @parameterized.expand(
         grid_parameters(
@@ -1955,6 +1960,8 @@ def test_pipeline_model_is_none(self):
 
         # compare model output class
         self.assertTrue(all(item["score"] > 0.0 for item in outputs))
+        del pipe
+        gc.collect()
 
     @parameterized.expand(
         grid_parameters(
@@ -2117,6 +2124,8 @@ def test_pipeline_model_is_none(self):
 
         # compare model output class
         self.assertTrue(all(all(isinstance(item, float) for item in row) for row in outputs[0]))
+        del pipe
+        gc.collect()
 
     @parameterized.expand(
         grid_parameters(
@@ -2561,10 +2570,11 @@ def test_pipeline_model_is_none(self):
         pipe = pipeline("text-generation")
         text = "My Name is Philipp and i live"
         outputs = pipe(text)
-
         # compare model output class
         self.assertIsInstance(outputs[0]["generated_text"], str)
         self.assertTrue(len(outputs[0]["generated_text"]) > len(text))
+        del pipe
+        gc.collect()
 
     @parameterized.expand(grid_parameters({"model_arch": SUPPORTED_ARCHITECTURES, "use_cache": [True]}))
     @require_torch_gpu
@@ -2976,6 +2986,8 @@ def test_pipeline_model_is_none(self):
         # compare model output class
         self.assertGreaterEqual(outputs[0]["score"], 0.0)
         self.assertTrue(isinstance(outputs[0]["label"], str))
+        del pipe
+        gc.collect()
 
     @parameterized.expand(
         grid_parameters(
@@ -3142,6 +3154,8 @@ def test_pipeline_model_is_none(self):
         # compare model output class
         self.assertTrue(outputs[0]["mask"] is not None)
         self.assertTrue(isinstance(outputs[0]["label"], str))
+        del pipe
+        gc.collect()
 
     # TODO: enable TensorrtExecutionProvider test once https://github.com/huggingface/optimum/issues/798 is fixed
     @parameterized.expand(
@@ -3327,6 +3341,8 @@ def test_pipeline_model_is_none(self):
         # compare model output class
         self.assertGreaterEqual(outputs[0]["score"], 0.0)
         self.assertIsInstance(outputs[0]["label"], str)
+        del pipe
+        gc.collect()
 
     @parameterized.expand(
         grid_parameters(
@@ -3970,6 +3986,8 @@ def test_pipeline_model_is_none(self):
         outputs = pipe(text, min_length=1, max_length=2)
         # compare model output class
         self.assertIsInstance(outputs[0]["translation_text"], str)
+        del pipe
+        gc.collect()
 
     @parameterized.expand(grid_parameters({"model_arch": SUPPORTED_ARCHITECTURES, "use_cache": [True]}))
     @require_torch_gpu