[Feat] Add Ovis-Image-7B text-to-image pipeline#1117
[Feat] Add Ovis-Image-7B text-to-image pipeline#1117HenryDzy wants to merge 4 commits intohao-ai-lab:mainfrom
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Summary of ChangesHello @HenryDzy, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request significantly expands the FastVideo framework by integrating the Ovis-Image-7B text-to-image model. It introduces new model architectures for the diffusion transformer and text encoder, along with their respective configurations and pipeline implementations. The changes enable users to perform high-quality text-to-image generation and fine-tune the Ovis-Image model within the FastVideo ecosystem. Additionally, the PR includes important refactorings to the model and pipeline registration systems, improving modularity and maintainability, and adds comprehensive test coverage to ensure the stability and correctness of the new features. Highlights
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Code Review
This is a great pull request that adds comprehensive support for the Ovis-Image-7B text-to-image model. The changes include native model implementations, configurations, a new pipeline, and a full suite of tests, which is excellent. The refactoring in the model and pipeline registries also helps to simplify the codebase. I've identified a few critical issues related to type correctness in configurations and hardcoded paths in tests and examples that need to be addressed. Once these are resolved, this will be a very solid contribution.
| def import_pipeline_classes( | ||
| pipeline_types: list[PipelineType] | PipelineType | None = None | ||
| ) -> dict[str, dict[str, type[ComposedPipelineBase] | None]]: | ||
| pipeline_types_key: tuple[PipelineType, ...] | PipelineType | None | ||
| if isinstance(pipeline_types, list): | ||
| pipeline_types_key = tuple(pipeline_types) | ||
| else: | ||
| pipeline_types_key = pipeline_types | ||
| return _import_pipeline_classes_cached(pipeline_types_key) | ||
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| @lru_cache | ||
| def _import_pipeline_classes_cached( | ||
| pipeline_types: tuple[PipelineType, ...] | PipelineType | None = None | ||
| ) -> dict[str, dict[str, type[ComposedPipelineBase] | None]]: | ||
| ) -> dict[str, dict[str, dict[str, type[ComposedPipelineBase] | None]]]: |
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The @lru_cache decorator requires all arguments to be hashable. The pipeline_types argument is typed as a list, which is not hashable and will raise a TypeError at runtime if a list is passed. To fix this, the function signature should be changed to accept a tuple instead of a list.
| def import_pipeline_classes( | |
| pipeline_types: list[PipelineType] | PipelineType | None = None | |
| ) -> dict[str, dict[str, type[ComposedPipelineBase] | None]]: | |
| pipeline_types_key: tuple[PipelineType, ...] | PipelineType | None | |
| if isinstance(pipeline_types, list): | |
| pipeline_types_key = tuple(pipeline_types) | |
| else: | |
| pipeline_types_key = pipeline_types | |
| return _import_pipeline_classes_cached(pipeline_types_key) | |
| @lru_cache | |
| def _import_pipeline_classes_cached( | |
| pipeline_types: tuple[PipelineType, ...] | PipelineType | None = None | |
| ) -> dict[str, dict[str, type[ComposedPipelineBase] | None]]: | |
| ) -> dict[str, dict[str, dict[str, type[ComposedPipelineBase] | None]]]: | |
| def import_pipeline_classes( | |
| pipeline_types: tuple[PipelineType, ...] | PipelineType | None = None | |
| ) -> dict[str, dict[str, dict[str, type[ComposedPipelineBase] | None]]]: |
| if isinstance(pipeline_types, list): | ||
| pipeline_types_to_scan = [ | ||
| pipeline_type.value for pipeline_type in pipeline_types | ||
| ] |
There was a problem hiding this comment.
Following the change to the function signature to accept a tuple for caching purposes, this check should be updated to look for a tuple instead of a list.
| if isinstance(pipeline_types, list): | |
| pipeline_types_to_scan = [ | |
| pipeline_type.value for pipeline_type in pipeline_types | |
| ] | |
| if isinstance(pipeline_types, tuple): | |
| pipeline_types_to_scan = [ | |
| pipeline_type.value for pipeline_type in pipeline_types | |
| ] |
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
1 participant
Adds native FastVideo support for Ovis-Image-7B
New files
Models & configs
fastvideo/models/dits/ovisimage.py— NativeOvisImageTransformer2DModel:6 double blocks + 27 single blocks, SwiGLU activations, RoPE,
DistributedAttentionfastvideo/models/encoders/qwen3.py—Qwen3Modeltext encoder(wraps
Ovis2.5-2Bfor conditioning)fastvideo/configs/pipelines/ovis_image.py—OvisImageT2IConfig(flow_shift=3.0, embedded_cfg_scale=5.0, Qwen3 pre/postprocess hooks)
fastvideo/pipelines/basic/ovis_image/—OvisImagePipelinePipeline
fastvideo/pipelines/basic/ovis_image/__init__.pyfastvideo/pipelines/basic/ovis_image/ovis_image_pipeline.pyfastvideo/training/ovis_image_training_pipeline.pyTests
fastvideo/tests/transformers/test_ovisimage.py— transformer forward passfastvideo/tests/encoders/test_qwen3_encoder.py— HF vs FastVideo Qwen3 parityfastvideo/tests/ssim/test_ovis_image_similarity.py— MS-SSIM regression testtests/local_tests/pipelines/test_ovis_image_pipeline_smoke.py— end-to-endVideoGeneratorsmoke testExample
examples/inference/basic/basic_ovis_image.py— runnable exampleFiles modified
fastvideo/registry.py— registeredAIDC-AI/Ovis-Image-7Bfastvideo/configs/models/dits/__init__.py— exportedOvisImageTransformer2DModelConfigfastvideo/configs/models/encoders/__init__.py— exportedQwen3Configfastvideo/configs/models/vaes/base.py— addedload_encoder/load_decoderfieldsfastvideo/models/registry.py— registeredOvisImageTransformer2DModel,Qwen3Modelfastvideo/pipelines/pipeline_registry.py— registeredOvisImagePipelinefastvideo/pipelines/stages/denoising.py—except (ImportError, RuntimeError)for Triton guardsfastvideo/pipelines/stages/causal_denoising.py— same fixfastvideo/pipelines/stages/matrixgame_denoising.py— same fixfastvideo/training/__init__.py— exportedOvisImageTrainingPipelinedocs/inference/support_matrix.md— added Ovis-Image-7B row