Use the Keras set_random_seed in tests (#30504)

Use the Keras set_random_seed to ensure reproducible weight initialization

tests/pipelines/test_pipelines_common.py

@@ -541,11 +541,10 @@ class PipelineUtilsTest(unittest.TestCase):
     @slow
     @require_tf
     def test_load_default_pipelines_tf(self):
-        import tensorflow as tf
-
+        from transformers.modeling_tf_utils import keras
         from transformers.pipelines import SUPPORTED_TASKS
 
-        set_seed_fn = lambda: tf.random.set_seed(0)  # noqa: E731
+        set_seed_fn = lambda: keras.utils.set_random_seed(0)  # noqa: E731
         for task in SUPPORTED_TASKS.keys():
             if task == "table-question-answering":
                 # test table in seperate test due to more dependencies
@@ -553,7 +552,7 @@ class PipelineUtilsTest(unittest.TestCase):
 
             self.check_default_pipeline(task, "tf", set_seed_fn, self.check_models_equal_tf)
 
-            # clean-up as much as possible GPU memory occupied by PyTorch
+            # clean-up as much as possible GPU memory occupied by TF
             gc.collect()
 
     @slow