[tests] fix vidtok tests (#13894)

* fix vidtok tests

* style

* Update tests/models/autoencoders/test_models_autoencoder_vidtok.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Apply style fixes

---------

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Author: 3 people

tests/models/autoencoders/test_models_autoencoder_vidtok.py

@@ -19,14 +19,24 @@
 from diffusers import AutoencoderVidTok
 from diffusers.utils.torch_utils import randn_tensor
 
-from ...testing_utils import IS_GITHUB_ACTIONS, enable_full_determinism, torch_device
+from ...testing_utils import enable_full_determinism, torch_device
 from ..testing_utils import BaseModelTesterConfig, MemoryTesterMixin, ModelTesterMixin, TrainingTesterMixin
 from .testing_utils import NewAutoencoderTesterMixin
 
 
 enable_full_determinism()
 
 
+def _run_nondeterministic(fn):
+    # avg_pool3d_backward_cuda has no deterministic CUDA implementation;
+    # temporarily relax the requirement for tests that do backward passes.
+    torch.use_deterministic_algorithms(False)
+    try:
+        fn()
+    finally:
+        torch.use_deterministic_algorithms(True)
+
+
 class AutoencoderVidTokTesterConfig(BaseModelTesterConfig):
     @property
     def model_class(self):
@@ -82,14 +92,25 @@ def test_gradient_checkpointing_is_applied(self):
         expected_set = {"VidTokEncoder3D", "VidTokDecoder3D"}
         super().test_gradient_checkpointing_is_applied(expected_set=expected_set)
 
-    @pytest.mark.skipif(IS_GITHUB_ACTIONS, reason="Skipping test inside GitHub Actions environment")
-    def test_layerwise_casting_training(self):
-        super().test_layerwise_casting_training()
+    def test_training(self):
+        _run_nondeterministic(super().test_training)
+
+    def test_training_with_ema(self):
+        _run_nondeterministic(super().test_training_with_ema)
+
+    def test_mixed_precision_training(self):
+        _run_nondeterministic(super().test_mixed_precision_training)
+
+    def test_gradient_checkpointing_equivalence(self):
+        _run_nondeterministic(super().test_gradient_checkpointing_equivalence)
 
 
 class TestAutoencoderVidTokMemory(AutoencoderVidTokTesterConfig, MemoryTesterMixin):
     """Memory optimization tests for AutoencoderVidTok."""
 
+    def test_layerwise_casting_training(self):
+        _run_nondeterministic(super().test_layerwise_casting_training)
+
 
 class TestAutoencoderVidTokSlicingTiling(AutoencoderVidTokTesterConfig, NewAutoencoderTesterMixin):
     """Slicing and tiling tests for AutoencoderVidTok."""