Update handler.py

handler.py

@@ -31,15 +31,13 @@ class EndpointHandler:
         prompts = data.pop("inputs", None)
         url = data.pop("image", None)
         seed = data.pop("seed", 0) 
-        num_inference_steps = data.pop("num_inference_steps",1)
-        
         response = requests.get(url)
         init_image = Image.open(BytesIO(response.content)).convert("RGB")
         #init_image = decode_base64_image(encoded_image)
         init_image.thumbnail((256, 256))
 
-        generator = [torch.Generator(device="cuda").manual_seed(i+seed) for i in range(num_inference_steps)]
-        images = self.pipe(prompts, init_image=init_image,num_inference_steps=num_inference_steps,generator = generator, **data).images
+        generator = torch.Generator(device="cuda").manual_seed(seed)
+        images = self.pipe(prompts, init_image=init_image,generator = generator, **data).images
         img_strs = []
 
         for image in images: