update

app.py

@@ -16,9 +16,15 @@ h1 {
   display: block;
 }
 """
+if torch.cuda.is_available():
+    device = "cuda"
+elif torch.backends.mps.is_available():
+    device = "mps"
+else:
+    device = "cpu"
 
 # Pipeline
-pipe = diffusers.StableDiffusionPipeline.from_pretrained("Lykon/DreamShaper").to("cuda", torch.float16)
+pipe = diffusers.StableDiffusionPipeline.from_pretrained("Lykon/DreamShaper").to(device, torch.float16)
 pipe.scheduler = diffusers.EulerDiscreteScheduler.from_config(pipe.scheduler.config)
 pipe.safety_checker = None
 
@@ -159,4 +165,4 @@ with gr.Blocks(css=css) as demo:
             gen.click(generate_merged, inputs=[prompt, seed, steps, height_width, negative_prompt,
                                         guidance_scale, method], outputs=[output_image, output_result])
 
-demo.launch(share=True)
+demo.launch(share=True)

merge.py

@@ -26,10 +26,13 @@ def init_generator(device: torch.device, fallback: torch.Generator = None):
     """
     Forks the current default random generator given device.
     """
+    print(f"init_generator device = {device}")
     if device.type == "cpu":
         return torch.Generator(device="cpu").set_state(torch.get_rng_state())
     elif device.type == "cuda":
         return torch.Generator(device=device).set_state(torch.cuda.get_rng_state())
+    elif device.type == "cuda":
+        return torch.Generator(device=device).set_state(torch.mps.get_rng_state())
     else:
         if fallback is None:
             return init_generator(torch.device("cpu"))

requirements.txt

@@ -1,4 +1,4 @@
 diffusers
 transformers
 accelerate
-xformers
+#xformers