- handler.py +3 -4
handler.py
CHANGED
@@ -32,12 +32,10 @@ class EndpointHandler():
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num_inference_steps = data.pop("num_inference_steps", 25)
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guidance_scale = data.pop("guidance_scale", 7.5)
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negative_prompt = data.pop("negative_prompt", None)
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-
height = data.pop("height", None)
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-
width = data.pop("width", None)
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strength = data.pop("strength", 0.7)
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denoising_start = data.pop("denoising_start_step", 0)
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-
denoising_end = data.pop("
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num_images_per_prompt = data.pop("num_images_per_prompt", 1)
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aesthetic_score = data.pop("aesthetic_score", 0.6)
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@@ -48,7 +46,8 @@ class EndpointHandler():
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else:
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image = None
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-
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# run inference pipeline
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out = self.pipe(inputs,
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image=image,
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num_inference_steps = data.pop("num_inference_steps", 25)
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guidance_scale = data.pop("guidance_scale", 7.5)
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negative_prompt = data.pop("negative_prompt", None)
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strength = data.pop("strength", 0.7)
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denoising_start = data.pop("denoising_start_step", 0)
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+
denoising_end = data.pop("denoising_end_step", 1)
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num_images_per_prompt = data.pop("num_images_per_prompt", 1)
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aesthetic_score = data.pop("aesthetic_score", 0.6)
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else:
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image = None
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+
print(f"Prompt: {inputs}, strength: {strength}, inf steps: {num_inference_steps}, denoise start: {denoising_start}, denoise_end: {denoising_end}")
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+
print(f"Imgs per prompt: {num_images_per_prompt}, aesthetic_score: {aesthetic_score}, guidance_scale: {guidance_scale}, negative_prompt: {negative_prompt}")
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# run inference pipeline
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out = self.pipe(inputs,
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image=image,
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