Removed test_audio_video_sync as it doesn't work as expected (#4050)

Author: prabhat00155

test/test_video_reader.py

@@ -1235,45 +1235,6 @@ def test_read_video_from_memory_scripted(self):
             )
             # FUTURE: check value of video / audio frames
 
-    def test_audio_video_sync(self):
-        """Test if audio/video are synchronised with pyav output."""
-        for test_video, config in test_videos.items():
-            full_path = os.path.join(VIDEO_DIR, test_video)
-            container = av.open(full_path)
-            if not container.streams.audio:
-                # Skip if no audio stream
-                continue
-            start_pts_val, cutoff = 0, 1
-            if container.streams.video:
-                video = container.streams.video[0]
-                arr = []
-                for index, frame in enumerate(container.decode(video)):
-                    if index == cutoff:
-                        start_pts_val = frame.pts
-                    if index >= cutoff:
-                        arr.append(frame.to_rgb().to_ndarray())
-                visual, _, info = io.read_video(full_path, start_pts=start_pts_val, pts_unit='pts')
-                self.assertAlmostEqual(
-                    config.video_fps, info['video_fps'], delta=0.0001
-                )
-                arr = torch.Tensor(arr)
-                if arr.shape == visual.shape:
-                    self.assertGreaterEqual(
-                        torch.mean(torch.isclose(visual.float(), arr, atol=1e-5).float()), 0.99)
-
-            container = av.open(full_path)
-            if container.streams.audio:
-                audio = container.streams.audio[0]
-                arr = []
-                for index, frame in enumerate(container.decode(audio)):
-                    if index >= cutoff:
-                        arr.append(frame.to_ndarray())
-                _, audio, _ = io.read_video(full_path, start_pts=start_pts_val, pts_unit='pts')
-                arr = torch.as_tensor(np.concatenate(arr, axis=1))
-                if arr.shape == audio.shape:
-                    self.assertGreaterEqual(
-                        torch.mean(torch.isclose(audio.float(), arr).float()), 0.99)
-
     def test_invalid_file(self):
         set_video_backend('video_reader')
         with self.assertRaises(RuntimeError):