[None][feat] Add FastWan2.2 TI2V-5B DMD pipeline (3-step text-to-video)#16162
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… golden Introduces FastWanPipeline for the FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers checkpoint — a CFG-free DMD-distilled text+image-to-video model built on Wan 2.2. Changes: - pipeline_fastwan.py: FastWanPipeline with 3-step DMD denoising loop - wan/defaults.py, wan/__init__.py, models/__init__.py: registry wiring - test_fastwan_dmd_math.py: unit tests for DMD timestep math (no checkpoint) - test_fastwan_registry.py: unit tests for pipeline registration and defaults - test_fastwan_pipeline.py: component accuracy tests (text encoder, VAE) - test_visual_gen.py: LPIPS regression test against 121-frame golden video - visual_gen_lpips_golden_media.zip: updated with 121-frame FastWan golden - l0_b200.yml: register all FastWan tests in CI Signed-off-by: Nnamdi Wankwo <knwankwo@nvidia.com> Signed-off-by: Kambili Nwankwo <67324523+Kambili@users.noreply.github.com>
Remove stray 'NVIDIA#112' prefix from the SPDX copyright line. Signed-off-by: Nnamdi Wankwo <knwankwo@nvidia.com> Signed-off-by: Kambili Nwankwo <67324523+Kambili@users.noreply.github.com>
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Description
Introduces
FastWanPipelinefor theFastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffuserscheckpoint — a CFG-free, DMD-distilled text-to-video model built on Wan 2.2 TI2V-5B.FastWan shares Wan 2.2 TI2V-5B's architecture exactly; only the distilled weights and the sampling recipe differ. The pipeline therefore subclasses
WanPipelineand overrides only the denoising loop, replacing the standard ~50-step diffusion with a 3-step DMD (Distribution Matching Distillation) schedule. This produces a 121×704×1280 video in ~3 denoising steps instead of ~50.Text-to-video only: FastWan2.2-5B's released weights are DMD-distilled for T2V, so the pipeline raises
NotImplementedErroron image input.Changes:
pipeline_fastwan.py: FastWanPipeline with the 3-step DMD denoising loopwan/defaults.py,wan/__init__.py,models/__init__.py: registry wiring for the WanDMDPipeline class and the HF checkpoint IDtest_fastwan_dmd_math.py: unit tests for the DMD timestep math (stubbed transformer, no checkpoint)test_fastwan_registry.py: unit tests for pipeline registration and default paramstest_fastwan_pipeline.py: component accuracy tests (text encoder, VAE)test_visual_gen.py: LPIPS regression test against a 121-frame golden referencevisual_gen_lpips_golden_media.zip: adds the 121-frame FastWan golden videol0_b200.yml: registers the FastWan tests in CITest Coverage
test_fastwan_registry.py— verifies WanDMDPipeline resolves to FastWanPipeline, the HF ID is registered, defaults are correct (3 steps, CFG-free), and image input raises NotImplementedError. (No checkpoint; image input test requires GPU for the nvtx_range decorator.)test_fastwan_dmd_math.py— verifies the DMD loop math with a stubbed transformer: sigma = t/1000 giving {1.0, 0.757, 0.522}, correct re-noising on intermediate steps, x0 kept on the final step, and output dtype.test_fastwan_pipeline.py— component-level accuracy checks (text encoder, VAE).test_visual_gen.py— end-to-end LPIPS regression: generates a 121-frame video with fixed settings and compares against the committed golden reference generated by FastVideo.l0_b200.yml— all of the above registered to run in CI on B200.