[Chore]: refactor out unused/redundant params in diffusion pipelines (#1235)

Signed-off-by: Huang, Zeyu <11222265+fhfuih@users.noreply.github.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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Zeyu Huang | 黃澤宇andHongsheng Liu authored and GitHub committed 2026-07-02 16:32:05 +02:00
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@@ -126,16 +126,16 @@ Call `self.diffuse` in your pipeline's forward function:
```python
import torch.nn as nn
from vllm_omni.diffusion.worker.request_batch import DiffusionRequestBatch
class YourModelPipeline(nn.Module, CFGParallelMixin):
def forward(
self,
prompt: str,
negative_prompt: str | None = None,
guidance_scale: float = 3.5,
num_inference_steps: int = 50,
**kwargs,
):
# Encode prompts, Initialize latents, Get timesteps
req: DiffusionRequestBatch,
) -> list[DiffusionOutput]:
# Read prompts and sampling params from the request
...
# Encode prompts, initialize latents, get timesteps
...
# Run diffusion loop (calls the mixin's diffuse method)
latents = self.diffuse(