[tests] xfail recent pipeline tests for specific methods. (#11469)

xfail recent pipeline tests for specific methods.

Author: sayakpaul

tests/pipelines/audioldm2/test_audioldm2.py

@@ -18,6 +18,7 @@
 import unittest
 
 import numpy as np
+import pytest
 import torch
 from transformers import (
     ClapAudioConfig,
@@ -44,7 +45,7 @@
     LMSDiscreteScheduler,
     PNDMScheduler,
 )
-from diffusers.utils.testing_utils import enable_full_determinism, nightly, torch_device
+from diffusers.utils.testing_utils import enable_full_determinism, is_torch_version, nightly, torch_device
 
 from ..pipeline_params import TEXT_TO_AUDIO_BATCH_PARAMS, TEXT_TO_AUDIO_PARAMS
 from ..test_pipelines_common import PipelineTesterMixin
@@ -474,6 +475,11 @@ def test_dict_tuple_outputs_equivalent(self):
         # increase tolerance from 1e-4 -> 3e-4 to account for large composite model
         super().test_dict_tuple_outputs_equivalent(expected_max_difference=3e-4)
 
+    @pytest.mark.xfail(
+        condition=is_torch_version(">=", "2.7"),
+        reason="Test currently fails on PyTorch 2.7.",
+        strict=False,
+    )
     def test_inference_batch_single_identical(self):
         # increase tolerance from 1e-4 -> 2e-4 to account for large composite model
         self._test_inference_batch_single_identical(expected_max_diff=2e-4)

tests/pipelines/i2vgen_xl/test_i2vgenxl.py

@@ -18,6 +18,7 @@
 import unittest
 
 import numpy as np
+import pytest
 import torch
 from transformers import (
     CLIPImageProcessor,
@@ -39,6 +40,7 @@
     backend_empty_cache,
     enable_full_determinism,
     floats_tensor,
+    is_torch_version,
     numpy_cosine_similarity_distance,
     require_torch_accelerator,
     skip_mps,
@@ -180,6 +182,11 @@ def test_text_to_video_default_case(self):
 
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
 
+    @pytest.mark.xfail(
+        condition=is_torch_version(">=", "2.7"),
+        reason="Test currently fails on PyTorch 2.7.",
+        strict=False,
+    )
     def test_save_load_local(self):
         super().test_save_load_local(expected_max_difference=0.006)