feat: ernie image/turbo

[Pfannkuchensack]

Summary

Adds Baidu ERNIE-Image and ERNIE-Image-Turbo (HF, HF Turbo) as a new BaseModelType, mirroring the FLUX.2 Klein and Z-Image integration patterns.

The two checkpoints share the same ErnieImageTransformer2DModel architecture (3072 hidden, 24 layers, 24 heads, Mistral3 text encoder, AutoencoderKLFlux2 VAE) and only differ in inference defaults (50 steps + CFG 4.0 vs. 8 steps + CFG 1.0 for Turbo), so they live under one BaseModelType.ErnieImage without a variant enum. The optional 3B Mistral3-based prompt enhancer that ships with the pipeline is wired through with a UI toggle.

This PR builds on top of #8859 (transformers 5.1+) and additionally bumps diffusers 0.36.0 → 0.38.0, which is the first release containing ErnieImagePipeline and ErnieImageTransformer2DModel.

Backend changes

• BaseModelType.ErnieImage, ModelType.PromptEnhancer, plus two new SubModelTypes (pe, pe_tokenizer) for the bundled prompt enhancer.
• Main_Diffusers_ErnieImage_Config and Main_Checkpoint_ErnieImage_Config with state-dict-based detection (x_embedder + text_proj + adaLN_modulation).
• A diffusers loader that loads transformer / vae / text_encoder / tokenizer plus optional pe / pe_tokenizer from a single pipeline directory.
• invokeai/backend/ernie_image/ with sampling utilities (2×2 patchify, BN normalize/denormalize, sigma schedule, padded text packing) and a rectified-flow denoise loop supporting Euler / Heun / LCM (reusing the FlowMatch* schedulers from FLUX).
• Five new invocations: ernie_image_model_loader, ernie_image_text_encoder (with prompt-enhancer toggle), ernie_image_denoise, ernie_image_vae_encode, ernie_image_vae_decode.
• ErnieImageConditioningInfo + conditioning field/output, including pickle allowlist for the disk serializer.
• Generation modes ernie_image_{txt2img,img2img,inpaint,outpaint}.
• Starter models for baidu/ERNIE-Image and baidu/ERNIE-Image-Turbo, plus a STARTER_BUNDLES entry.

Frontend changes

• services/api/schema.ts regenerated to expose the new node types.
• Type unions extended (ImageOutput, LatentToImage, ImageToLatents, DenoiseLatents, MainModelLoaderNodes).
• ParamsState gains ernieImageScheduler and ernieImageUsePromptEnhancer, with reducers, selectors, and selectIsErnieImage.
• buildErnieImageGraph (txt2img / img2img / inpaint / outpaint) wired into useEnqueueCanvas.
• ERNIE entries added to MODEL_BASE_TO_{COLOR,LONG_NAME,SHORT_NAME}; prompt_enhancer added to MODEL_TYPE_TO_LONG_NAME.
• ParamErnieImageScheduler and ParamErnieImagePromptEnhancer rendered conditionally in GenerationSettingsAccordion.
• All add{TextTo,ImageTo,Inpaint,Outpaint}Image rectified-flow type guards extended to accept ernie_image_denoise; isMainModelWithoutUnet likewise.

Diffusers 0.38 fix-out

• hotfixes.py: import LoRACompatibleConv directly. The lazy module loader in 0.38 no longer exposes diffusers.models.lora as an attribute, so the legacy patch path crashes on import.
• pyproject.toml declares prerelease = "allow" under [tool.uv], with a comment explaining that diffusers 0.38.0 itself hard-pins safetensors>=0.8.0-rc.0. We can drop this again once a diffusers patch release ships with a stable safetensors floor.

Related Issues / Discussions

• Builds on Update to transformers 5.1.0 #8859 (transformers 5.1.0).
• Diffusers 0.38.0 release notes: https://github.com/huggingface/diffusers/releases/tag/v0.38.0
• Baidu ERNIE-Image: https://huggingface.co/baidu/ERNIE-Image / https://huggingface.co/baidu/ERNIE-Image-Turbo

QA Instructions

Automated

• pytest tests/ -m "not slow" — passes (619 / 619, the same tests/model_identification LFS-skip as on main).
• pnpm lint:tsc, pnpm lint:eslint, pnpm lint:prettier — all clean.
• pnpm test:no-watch — 563 / 563 frontend tests pass.

Manual smoketest of pre-existing models (regression for the diffusers / transformers bump)

Pick at least two of these and run a single txt2img each. Confirm no crashes and visually-plausible output:

• SDXL
• FLUX.1 Dev
• FLUX.2 Klein
• SD3
• Z-Image-Turbo

Plus the relevant items from #8859's test plan: SD 1.5 prompt-weighted generation (compel path), FLUX text-to-image (T5 tokenizer path), HF model install via repo ID, NSFW checker first-time download.

Manual smoketest of ERNIE-Image (requires a GPU — 8B parameters)

1. Install baidu/ERNIE-Image-Turbo from the new starter bundle. The Model Manager should classify it as BaseModelType.ErnieImage.
2. Pick the model on the Generate tab. Confirm the scheduler dropdown and Prompt Enhancer toggle appear in the Generation accordion.
3. txt2img at 1024×1024, 8 steps, CFG 1.0 — should produce an image.
4. Toggle the prompt enhancer on with a short prompt (e.g. "a fox"); the enhancer log line in the backend should show a rewritten longer prompt before encoding.
5. Repeat with baidu/ERNIE-Image (50 steps, CFG 4.0).
6. img2img / inpaint / outpaint — one run each on the canvas tab.

Merge Plan

• This PR depends on Update to transformers 5.1.0 #8859 being merged first (or being merged in together, since they share the transformers>=5.1.0 override). I have no preference; happy to rebase whenever Update to transformers 5.1.0 #8859 lands.
• After this PR merges, a follow-up release should call out the diffusers and transformers major bumps in the changelog. The ERNIE-Image starter bundle is gated behind those bumps.
• The prerelease = "allow" line in pyproject.toml is a temporary measure tied to diffusers 0.38.0's safetensors>=0.8.0-rc.0 upstream pin. Worth revisiting (and removing) once a diffusers patch release relaxes that requirement.

Checklist

• The PR has a short but descriptive title, suitable for a changelog
• Tests added / updated (if applicable) — backend regression suite covers the new code paths via existing model-config and loader-registry tests; no new dedicated unit tests for the ERNIE sampling helpers (the patchify roundtrip was sanity-checked manually).
• ❗Changes to a redux slice have a corresponding migration — N/A: only additive fields with defaults in paramsSlice.
• Documentation added / updated (if applicable) — none yet; the docs-old/contributing/NEW_MODEL_INTEGRATION.md checklist describes the integration shape this PR follows.
• Updated What's New copy (if doing a release after this PR)

Out of scope (planned follow-ups)

• ControlNet, IP-Adapter, and LoRA support for ERNIE-Image.
• Single-file checkpoint loading (the Main_Checkpoint_ErnieImage_Config is in place as defensive scaffolding, but the loader currently raises NotImplementedError for that format).
• Metadata recall handlers in the gallery side panel for ERNIE-specific parameters.