huggingface / huggingface/diffusers
PixArtSigmaPipeline: no LoRA loading support
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Beschreibung
### Describe the bug
~~Calling `pipe.load_lora_weights(...)` on `ErnieImagePipeline` raises `AttributeError: 'ErnieImagePipeline' object has no attribute 'load_lora_weights'`. Neither the pipeline nor its denoiser, `ErnieImageTransformer2DModel`, currently has LoRA support wired up:~~
- ~~`ErnieImagePipeline` doesn't inherit a `*LoraLoaderMixin` (checked the registry in `diffusers/loaders/lora_pipeline.py` — there's no `ErnieLoraLoaderMixin`, unlike the ~20 other architectures that have one: SD, SDXL, SD3, Flux, Sana, Lumina2, QwenImage, ZImage, HiDream, etc.).~~
- ~~`ErnieImageTransformer2DModel` doesn't inherit `PeftAdapterMixin`, so there's no `transformer.add_adapter()` route either.~~
**Side note, same gap, another model:** `PixArtSigmaPipeline` is in the same spot — no `*LoraLoaderMixin`, and `PixArtTransformer2DModel` has no `PeftAdapterMixin` either. But that one's been around since early 2024 (#7654) without LoRA support landing since.
### Reproduction
```python
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("path/to/lora.safetensors")
```
```
AttributeError: 'ErnieImagePipeline' object has no attribute 'load_lora_weights'
```
The same call on `PixArtSigmaPipeline.from_pretrained("PixArt-alpha/PixArt-Sigma-XL-2-1024-MS")` hits the identical `AttributeError`.
### Logs
```
AttributeError: 'ErnieImagePipeline' object has no attribute 'load_lora_weights'
```
### System Info
- diffusers commit: 0f1abc4ae8b0eb2a3b40e82a310507281144c423 (main)
- Python: 3.12
- Platform: Linux
### Who can help?
@yiyixuxu @sayakpaul
Beitragsleitfaden
Rechercherichtung
Beginne mit diffusers/loaders/lora_pipeline.py und untersuche anschließend ErnieImagePipeline, PixArtSigmaPipeline, ErnieImageTransformer2DModel und PixArtTransformer2DModel. Führe zuerst die gemeldeten Reproduktionen von load_lora_weights aus. Die Aufgabe ist abgeschlossen, wenn die betroffenen Pipelines und Denoiser den angeforderten LoRA-Ladepfad ohne den gemeldeten AttributeError unterstützen.
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Bewertung
- Tech-Stack
- python, pytorch
- Bereich
- machine-learning
- Issue-Typ
- Feature
- Schwierigkeit
- 4/5
- Geschätzter Aufwand
- 3-5 Tage
- Aktivitätsstatus
- Ruhig
- Klarheit
- Größtenteils klar
- Anfängerfreundlichkeit
- 43/100