test without decoder StableCascadePipeline

handler.py

@@ -4,7 +4,7 @@ from PIL import Image
 from io import BytesIO
 from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
 from diffusers import StableDiffusionPipeline
-from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
+from diffusers import StableCascadePipeline, StableCascadePriorPipeline
 
 import torch
 
@@ -19,10 +19,9 @@ dtype = torch.bfloat16 if torch.cuda.get_device_capability()[0] == 8 else torch.
 class EndpointHandler():
      def __init__(self, path=""):
          self.stable_diffusion_id = "Lykon/dreamshaper-8"
-         self.pipe = StableDiffusionPipeline.from_pretrained(self.stable_diffusion_id,torch_dtype=dtype,safety_checker=StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker", torch_dtype=dtype)).to(device.type)
 
          self.prior_pipeline = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=dtype)#.to(device)
-         self.decoder_pipeline = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade",  torch_dtype=dtype)#.to(device) 
+         self.decoder_pipeline = StableCascadePipeline.from_pretrained("stabilityai/stable-cascade",  torch_dtype=dtype)#.to(device) 
 
 
          self.generator = torch.Generator(device=device.type).manual_seed(3)
@@ -39,18 +38,6 @@ class EndpointHandler():
         height = data.pop("height", None)
         width = data.pop("width", None)
 
-        # # run inference pipeline
-        #  out = self.pipe(
-        #     prompt=prompt, 
-        #     negative_prompt=negative_prompt,
-        #     num_inference_steps=num_inference_steps, 
-        #     guidance_scale=guidance_scale,
-        #     num_images_per_prompt=1,
-        #     height=height,
-        #     width=width,
-        #     generator=self.generator
-        # )
-        
         self.prior_pipeline.to(device)
         self.decoder_pipeline.to(device)