[CI] Refactor SD3 Transformer Test#13340
Merged
Merged
Conversation
sayakpaul
reviewed
Mar 27, 2026
Comment on lines
+26
to
+27
| TorchAoTesterMixin, | ||
| TorchCompileTesterMixin, |
Member
There was a problem hiding this comment.
I don't think we ever had these in the legacy tests? If so, let's not include them.
Collaborator
Author
There was a problem hiding this comment.
I think this points to a gap in the previous testing. Let's keep the coverage since SD3.5 is reasonably popular.
sayakpaul
reviewed
Mar 27, 2026
sayakpaul
left a comment
Member
There was a problem hiding this comment.
Let's not include compilation and TorchAO tests if didn't have them in the legacy.
DN6
added a commit
that referenced
this pull request
Jun 10, 2026
* update * update --------- Co-authored-by: Sayak Paul <[email protected]>
sayakpaul
added a commit
that referenced
this pull request
Jun 16, 2026
* update * update * update * update * [CI] Refactor SD3 Transformer Test (#13340) * update * update --------- Co-authored-by: Sayak Paul <[email protected]> * refactor unet tests (3d_condition, motion, controlnetxs) (#13897) * refactor unet_3d_condition tests * refactor unet_motion tests * refactor unet_controlnetxs tests * refactor unet_1d tests (#13898) * refactor unet_1d tests * use per-sample output_shape for unet_1d tests --------- Co-authored-by: Sayak Paul <[email protected]> * refactor unet_2d tests (#13901) Co-authored-by: Sayak Paul <[email protected]> * [chore] log quant config to the user_agent (#13850) log quant config to the user_agent * Integrate AutoRound into Diffusers (#13552) * support auto_round Signed-off-by: Xin He <[email protected]> * add document and unit tests Signed-off-by: Xin He <[email protected]> * fix CI Signed-off-by: Xin He <[email protected]> * Apply suggestions from code review Co-authored-by: Steven Liu <[email protected]> * update document and overwrite the default quantization_config with specified backend. Signed-off-by: Xin He <[email protected]> * add UT and fix bug Signed-off-by: Xin He <[email protected]> * update per comments Signed-off-by: Xin He <[email protected]> * update per comments Signed-off-by: Xin He <[email protected]> * fix compile error in doc Signed-off-by: Xin He <[email protected]> * Apply style fixes * small nits * Add auto_round dependency to the versions table Signed-off-by: Xin He <[email protected]> * fix make deps_table_check_updated Signed-off-by: Xin He <[email protected]> * fix CI Signed-off-by: Xin He <[email protected]> --------- Signed-off-by: Xin He <[email protected]> Co-authored-by: Steven Liu <[email protected]> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Sayak Paul <[email protected]> * [tests] refactor UNet model tests to align with the new pattern (#13153) * refactor unet2d condition model tests. * fix tests * up * fix * Revert "fix" This reverts commit 46d44b7. * up * recompile limit * [tests] refactor test_models_unet_1d.py to use modular testing mixins Refactor UNet1D model tests to follow the modern testing pattern using BaseModelTesterConfig and focused mixin classes (ModelTesterMixin, MemoryTesterMixin, TrainingTesterMixin, LoraTesterMixin). Both UNet1D standard and RL variants now have separate config classes and dedicated test classes organized by concern (core, memory, training, LoRA, hub loading). Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_2d.py to use modular testing mixins Refactor UNet2D model tests (standard, LDM, NCSN++) to follow the modern testing pattern. Each variant gets its own config class and dedicated test classes organized by concern (core, memory, training, LoRA, hub loading). Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_3d_condition.py to use modular testing mixins Refactor UNet3DConditionModel tests to follow the modern testing pattern with separate classes for core, attention, memory, training, and LoRA. Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_controlnetxs.py to use modular testing mixins Refactor UNetControlNetXSModel tests to follow the modern testing pattern with separate classes for core, memory, training, and LoRA. Specialized tests (from_unet, freeze_unet, forward_no_control, time_embedding_mixing) remain in the core test class. Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_spatiotemporal.py to use modular testing mixins Refactored the spatiotemporal UNet test file to follow the modern modular testing pattern with BaseModelTesterConfig and focused test classes: - UNetSpatioTemporalTesterConfig: Base configuration with model setup - TestUNetSpatioTemporal: Core model tests (ModelTesterMixin, UNetTesterMixin) - TestUNetSpatioTemporalAttention: Attention-related tests (AttentionTesterMixin) - TestUNetSpatioTemporalMemory: Memory/offloading tests (MemoryTesterMixin) - TestUNetSpatioTemporalTraining: Training tests (TrainingTesterMixin) - TestUNetSpatioTemporalLoRA: LoRA adapter tests (LoraTesterMixin) Co-Authored-By: Claude Opus 4.6 <[email protected]> * remove test suites that are passed. * fix consistencydecodervae tests * Revert "fix consistencydecodervae tests" This reverts commit 41b036b. --------- Co-authored-by: Claude Opus 4.6 <[email protected]> Co-authored-by: dg845 <[email protected]> * [tests] fix vidtok tests (#13894) * fix vidtok tests * style * Update tests/models/autoencoders/test_models_autoencoder_vidtok.py Co-authored-by: dg845 <[email protected]> * Apply style fixes --------- Co-authored-by: dg845 <[email protected]> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * clean up --------- Signed-off-by: Xin He <[email protected]> Co-authored-by: Sayak Paul <[email protected]> Co-authored-by: Akshan Krithick <[email protected]> Co-authored-by: Xin He <[email protected]> Co-authored-by: Steven Liu <[email protected]> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 <[email protected]> Co-authored-by: dg845 <[email protected]>
DN6
added a commit
that referenced
this pull request
Jul 1, 2026
* update * update --------- Co-authored-by: Sayak Paul <[email protected]>
DN6
added a commit
that referenced
this pull request
Jul 1, 2026
* update * update * update * update * [CI] Refactor SD3 Transformer Test (#13340) * update * update --------- Co-authored-by: Sayak Paul <[email protected]> * refactor unet tests (3d_condition, motion, controlnetxs) (#13897) * refactor unet_3d_condition tests * refactor unet_motion tests * refactor unet_controlnetxs tests * refactor unet_1d tests (#13898) * refactor unet_1d tests * use per-sample output_shape for unet_1d tests --------- Co-authored-by: Sayak Paul <[email protected]> * refactor unet_2d tests (#13901) Co-authored-by: Sayak Paul <[email protected]> * [chore] log quant config to the user_agent (#13850) log quant config to the user_agent * Integrate AutoRound into Diffusers (#13552) * support auto_round Signed-off-by: Xin He <[email protected]> * add document and unit tests Signed-off-by: Xin He <[email protected]> * fix CI Signed-off-by: Xin He <[email protected]> * Apply suggestions from code review Co-authored-by: Steven Liu <[email protected]> * update document and overwrite the default quantization_config with specified backend. Signed-off-by: Xin He <[email protected]> * add UT and fix bug Signed-off-by: Xin He <[email protected]> * update per comments Signed-off-by: Xin He <[email protected]> * update per comments Signed-off-by: Xin He <[email protected]> * fix compile error in doc Signed-off-by: Xin He <[email protected]> * Apply style fixes * small nits * Add auto_round dependency to the versions table Signed-off-by: Xin He <[email protected]> * fix make deps_table_check_updated Signed-off-by: Xin He <[email protected]> * fix CI Signed-off-by: Xin He <[email protected]> --------- Signed-off-by: Xin He <[email protected]> Co-authored-by: Steven Liu <[email protected]> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Sayak Paul <[email protected]> * [tests] refactor UNet model tests to align with the new pattern (#13153) * refactor unet2d condition model tests. * fix tests * up * fix * Revert "fix" This reverts commit 46d44b7. * up * recompile limit * [tests] refactor test_models_unet_1d.py to use modular testing mixins Refactor UNet1D model tests to follow the modern testing pattern using BaseModelTesterConfig and focused mixin classes (ModelTesterMixin, MemoryTesterMixin, TrainingTesterMixin, LoraTesterMixin). Both UNet1D standard and RL variants now have separate config classes and dedicated test classes organized by concern (core, memory, training, LoRA, hub loading). Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_2d.py to use modular testing mixins Refactor UNet2D model tests (standard, LDM, NCSN++) to follow the modern testing pattern. Each variant gets its own config class and dedicated test classes organized by concern (core, memory, training, LoRA, hub loading). Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_3d_condition.py to use modular testing mixins Refactor UNet3DConditionModel tests to follow the modern testing pattern with separate classes for core, attention, memory, training, and LoRA. Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_controlnetxs.py to use modular testing mixins Refactor UNetControlNetXSModel tests to follow the modern testing pattern with separate classes for core, memory, training, and LoRA. Specialized tests (from_unet, freeze_unet, forward_no_control, time_embedding_mixing) remain in the core test class. Co-Authored-By: Claude Opus 4.6 <[email protected]> * [tests] refactor test_models_unet_spatiotemporal.py to use modular testing mixins Refactored the spatiotemporal UNet test file to follow the modern modular testing pattern with BaseModelTesterConfig and focused test classes: - UNetSpatioTemporalTesterConfig: Base configuration with model setup - TestUNetSpatioTemporal: Core model tests (ModelTesterMixin, UNetTesterMixin) - TestUNetSpatioTemporalAttention: Attention-related tests (AttentionTesterMixin) - TestUNetSpatioTemporalMemory: Memory/offloading tests (MemoryTesterMixin) - TestUNetSpatioTemporalTraining: Training tests (TrainingTesterMixin) - TestUNetSpatioTemporalLoRA: LoRA adapter tests (LoraTesterMixin) Co-Authored-By: Claude Opus 4.6 <[email protected]> * remove test suites that are passed. * fix consistencydecodervae tests * Revert "fix consistencydecodervae tests" This reverts commit 41b036b. --------- Co-authored-by: Claude Opus 4.6 <[email protected]> Co-authored-by: dg845 <[email protected]> * [tests] fix vidtok tests (#13894) * fix vidtok tests * style * Update tests/models/autoencoders/test_models_autoencoder_vidtok.py Co-authored-by: dg845 <[email protected]> * Apply style fixes --------- Co-authored-by: dg845 <[email protected]> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * clean up --------- Signed-off-by: Xin He <[email protected]> Co-authored-by: Sayak Paul <[email protected]> Co-authored-by: Akshan Krithick <[email protected]> Co-authored-by: Xin He <[email protected]> Co-authored-by: Steven Liu <[email protected]> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 <[email protected]> Co-authored-by: dg845 <[email protected]>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
What does this PR do?
Fixes # (issue)
Before submitting
documentation guidelines, and
here are tips on formatting docstrings.
Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.