fix(api): positional args for LPW pipeline
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@ -247,17 +247,17 @@ def run_txt2img_pipeline(model, provider, scheduler, prompt, negative_prompt, cf
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print('saved txt2img output: %s' % (output))
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print('saved txt2img output: %s' % (output))
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def run_img2img_pipeline(model, provider, scheduler, prompt, negative_prompt, cfg, steps, seed, output, strength, input_image):
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def run_img2img_pipeline(model, provider, scheduler, prompt, negative_prompt, cfg, steps, seed, output, strength, source_image):
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pipe = load_pipeline(OnnxStableDiffusionImg2ImgPipeline,
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pipe = load_pipeline(OnnxStableDiffusionImg2ImgPipeline,
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model, provider, scheduler)
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model, provider, scheduler)
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rng = np.random.RandomState(seed)
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rng = np.random.RandomState(seed)
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image = pipe.img2img(
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image = pipe.img2img(
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source_image,
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prompt,
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prompt,
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generator=rng,
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generator=rng,
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guidance_scale=cfg,
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guidance_scale=cfg,
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image=input_image,
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negative_prompt=negative_prompt,
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negative_prompt=negative_prompt,
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num_inference_steps=steps,
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num_inference_steps=steps,
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strength=strength,
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strength=strength,
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@ -280,13 +280,13 @@ def run_inpaint_pipeline(model, provider, scheduler, prompt, negative_prompt, cf
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source_image, mask_image, (left, right, top, bottom))
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source_image, mask_image, (left, right, top, bottom))
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image = pipe.inpaint(
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image = pipe.inpaint(
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source_image,
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mask_image,
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prompt,
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prompt,
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generator=rng,
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generator=rng,
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guidance_scale=cfg,
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guidance_scale=cfg,
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height=height,
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height=height,
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image=source_image,
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latents=latents,
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latents=latents,
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mask_image=mask_image,
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negative_prompt=negative_prompt,
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negative_prompt=negative_prompt,
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num_inference_steps=steps,
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num_inference_steps=steps,
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width=width,
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width=width,
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