Spaces:
Running
Running
Allow changing LoRA scaling alpha
Browse files- app_inference.py +6 -0
- inference.py +8 -4
app_inference.py
CHANGED
@@ -99,6 +99,11 @@ def create_inference_demo(pipe: InferencePipeline,
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max_lines=1,
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placeholder='Example: "A picture of a sks dog in a bucket"'
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)
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seed = gr.Slider(label='Seed',
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minimum=0,
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maximum=100000,
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@@ -149,6 +154,7 @@ def create_inference_demo(pipe: InferencePipeline,
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inputs = [
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lora_model_id,
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prompt,
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seed,
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num_steps,
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guidance_scale,
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max_lines=1,
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placeholder='Example: "A picture of a sks dog in a bucket"'
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)
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+
alpha = gr.Slider(label='LoRA alpha',
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+
minimum=0,
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+
maximum=2,
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step=0.05,
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value=1)
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seed = gr.Slider(label='Seed',
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minimum=0,
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maximum=100000,
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inputs = [
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lora_model_id,
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prompt,
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alpha,
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seed,
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num_steps,
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guidance_scale,
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inference.py
CHANGED
@@ -73,6 +73,7 @@ class InferencePipeline:
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self,
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lora_model_id: str,
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prompt: str,
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seed: int,
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n_steps: int,
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guidance_scale: float,
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@@ -83,8 +84,11 @@ class InferencePipeline:
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self.load_pipe(lora_model_id)
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generator = torch.Generator(device=self.device).manual_seed(seed)
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-
out = self.pipe(
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-
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-
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-
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return out.images[0]
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self,
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lora_model_id: str,
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prompt: str,
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lora_scale: float,
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seed: int,
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n_steps: int,
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guidance_scale: float,
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self.load_pipe(lora_model_id)
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generator = torch.Generator(device=self.device).manual_seed(seed)
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out = self.pipe(
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prompt,
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num_inference_steps=n_steps,
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guidance_scale=guidance_scale,
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generator=generator,
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cross_attention_kwargs={'scale': lora_scale},
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) # type: ignore
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return out.images[0]
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