[to #42322933] relax un-determinsitic test validation constraints

放松了tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py里面对于识别非determinsitic的校验条件，一方便后续模型更新
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10245940

tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py

@@ -15,7 +15,7 @@ class EasyCVSegmentationPipelineTest(unittest.TestCase):
 
     img_path = 'data/test/images/image_segmentation.jpg'
 
-    def _internal_test__(self, model_id):
+    def _internal_test_(self, model_id):
         img = np.asarray(Image.open(self.img_path))
 
         semantic_seg = pipeline(task=Tasks.image_segmentation, model=model_id)
@@ -26,12 +26,8 @@ class EasyCVSegmentationPipelineTest(unittest.TestCase):
         results = outputs[0]
         self.assertListEqual(
             list(img.shape)[:2], list(results['seg_pred'].shape))
-        self.assertListEqual(results['seg_pred'][1, 4:10].tolist(),
-                             [161 for i in range(6)])
-        self.assertListEqual(results['seg_pred'][-1, -10:].tolist(),
-                             [133 for i in range(10)])
 
-    def _internal_test_batch(self, model_id, num_samples=2, batch_size=2):
+    def _internal_test_batch_(self, model_id, num_samples=2, batch_size=2):
         # TODO: support in the future
         img = np.asarray(Image.open(self.img_path))
         num_samples = num_samples
@@ -48,40 +44,42 @@ class EasyCVSegmentationPipelineTest(unittest.TestCase):
         for output in outputs:
             self.assertListEqual(
                 list(img.shape)[:2], list(output['seg_pred'].shape))
-            self.assertListEqual(output['seg_pred'][1, 4:10].tolist(),
-                                 [161 for i in range(6)])
-            self.assertListEqual(output['seg_pred'][-1, -10:].tolist(),
-                                 [133 for i in range(10)])
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b0(self):
         model_id = 'damo/cv_segformer-b0_image_semantic-segmentation_coco-stuff164k'
-        self._internal_test__(model_id)
+        self._internal_test_(model_id)
+        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b1(self):
         model_id = 'damo/cv_segformer-b1_image_semantic-segmentation_coco-stuff164k'
-        self._internal_test__(model_id)
+        self._internal_test_(model_id)
+        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b2(self):
         model_id = 'damo/cv_segformer-b2_image_semantic-segmentation_coco-stuff164k'
-        self._internal_test__(model_id)
+        self._internal_test_(model_id)
+        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b3(self):
         model_id = 'damo/cv_segformer-b3_image_semantic-segmentation_coco-stuff164k'
-        self._internal_test__(model_id)
+        self._internal_test_(model_id)
+        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b4(self):
         model_id = 'damo/cv_segformer-b4_image_semantic-segmentation_coco-stuff164k'
-        self._internal_test__(model_id)
+        self._internal_test_(model_id)
+        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b5(self):
         model_id = 'damo/cv_segformer-b5_image_semantic-segmentation_coco-stuff164k'
-        self._internal_test__(model_id)
+        self._internal_test_(model_id)
+        self._internal_test_batch_(model_id)
 
 
 if __name__ == '__main__':