Files
InvokeAI/invokeai/app
Alexander Eichhorn 689953e3cf Feature/zimage scheduler support (#8705)
* feat(flux): add scheduler selection for Flux models

Add support for alternative diffusers Flow Matching schedulers:
- Euler (default, 1st order)
- Heun (2nd order, better quality, 2x slower)
- LCM (optimized for few steps)

Backend:
- Add schedulers.py with scheduler type definitions and class mapping
- Modify denoise.py to accept optional scheduler parameter
- Add scheduler InputField to flux_denoise invocation (v4.2.0)

Frontend:
- Add fluxScheduler to Redux state and paramsSlice
- Create ParamFluxScheduler component for Linear UI
- Add scheduler to buildFLUXGraph for generation

* feat(z-image): add scheduler selection for Z-Image models

Add support for alternative diffusers Flow Matching schedulers for Z-Image:
- Euler (default) - 1st order, optimized for Z-Image-Turbo (8 steps)
- Heun (2nd order) - Better quality, 2x slower
- LCM - Optimized for few-step generation

Backend:
- Extend schedulers.py with Z-Image scheduler types and mapping
- Add scheduler InputField to z_image_denoise invocation (v1.3.0)
- Refactor denoising loop to support diffusers schedulers

Frontend:
- Add zImageScheduler to Redux state in paramsSlice
- Create ParamZImageScheduler component for Linear UI
- Add scheduler to buildZImageGraph for generation

* fix ruff check

* fix(schedulers): prevent progress percentage overflow with LCM scheduler

LCM scheduler may have more internal timesteps than user-facing steps,
causing user_step to exceed total_steps. This resulted in progress
percentage > 1.0, which caused a pydantic validation error.

Fix: Only call step_callback when user_step <= total_steps.

* Ruff format

* fix(schedulers): remove initial step-0 callback for consistent step count

Remove the initial step_callback at step=0 to match SD/SDXL behavior.
Previously Flux/Z-Image showed N+1 steps (step 0 + N denoising steps),
while SD/SDXL showed only N steps. Now all models display N steps
consistently in the server log.

* feat(z-image): add scheduler support with metadata recall

- Handle LCM scheduler by using num_inference_steps instead of custom sigmas
- Fix progress bar to show user-facing steps instead of internal scheduler steps
- Pass scheduler parameter to Z-Image denoise node in graph builder
- Add model-aware metadata recall for Flux and Z-Image schedulers

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Co-authored-by: Jonathan <34005131+JPPhoto@users.noreply.github.com>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
2026-01-03 20:37:04 +00:00
..
2025-10-15 10:46:16 +11:00
2025-05-30 19:03:43 +10:00