From fd41e2daf4cc61af085ece25fab79ef4fd7ec5b4 Mon Sep 17 00:00:00 2001
From: Lysandre Debut <lysandre@huggingface.co>
Date: Mon, 12 Jul 2021 17:42:59 +0200
Subject: [PATCH] Pipeline should be agnostic (#12656)

---
 tests/test_pipelines_question_answering.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/tests/test_pipelines_question_answering.py b/tests/test_pipelines_question_answering.py
index 9c02640683..af3ca91c04 100644
--- a/tests/test_pipelines_question_answering.py
+++ b/tests/test_pipelines_question_answering.py
@@ -14,6 +14,7 @@
 
 import unittest
 
+from transformers import is_tf_available, is_torch_available
 from transformers.data.processors.squad import SquadExample
 from transformers.pipelines import Pipeline, QuestionAnsweringArgumentHandler, pipeline
 from transformers.testing_utils import slow
@@ -57,7 +58,7 @@ class QAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
                 task=self.pipeline_task,
                 model=model,
                 tokenizer=model,
-                framework="pt",
+                framework="pt" if is_torch_available() else "tf",
                 **self.pipeline_loading_kwargs,
             )
             for model in self.small_models
@@ -65,6 +66,7 @@ class QAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
         return question_answering_pipelines
 
     @slow
+    @unittest.skipIf(not is_torch_available() and not is_tf_available(), "Either torch or TF must be installed.")
     def test_high_topk_small_context(self):
         self.pipeline_running_kwargs.update({"topk": 20})
         valid_inputs = [