[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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@@ -126,16 +126,16 @@ Call `self.diffuse` in your pipeline's forward function:
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```python
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import torch.nn as nn
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from vllm_omni.diffusion.worker.request_batch import DiffusionRequestBatch
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class YourModelPipeline(nn.Module, CFGParallelMixin):
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def forward(
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self,
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prompt: str,
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negative_prompt: str | None = None,
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guidance_scale: float = 3.5,
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num_inference_steps: int = 50,
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**kwargs,
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):
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# Encode prompts, Initialize latents, Get timesteps
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req: DiffusionRequestBatch,
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) -> list[DiffusionOutput]:
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# Read prompts and sampling params from the request
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...
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# Encode prompts, initialize latents, get timesteps
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...
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# Run diffusion loop (calls the mixin's diffuse method)
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latents = self.diffuse(
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