AI/diffusers
1
0
Fork 0
mirror of https://github.com/huggingface/diffusers.git synced 2026-10-27 21:33:02 +03:00
Code Activity

[tests] fix vidtok tests (#13894)

Browse Source 
* 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>
This commit is contained in:
Sayak Paul
2026-06-10 13:35:29 +05:30
committed by GitHub
parent 1c7f759d84
commit 76e7d164a5
1 changed files with 25 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

29
tests/models/autoencoders/test_models_autoencoder_vidtok.py
View File

@@ -19,7 +19,7 @@ import torch
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
@@ -27,6 +27,16 @@ 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 @@ class TestAutoencoderVidTokTraining(AutoencoderVidTokTesterConfig, TrainingTeste
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."""