Make inference slightly faster.

app.py

@@ -39,14 +39,14 @@ with gr.Blocks(css=".container { max-width: 800px; margin: auto; }") as demo:
         result = defaultdict(list)
         for _, seed in zip_longest(range(n), seeds, fillvalue=None):
             seed = random.randint(0, 2**32 - 1) if seed is None else seed
-            print(f"Setting seed {seed}")
             _ = torch.manual_seed(seed)
-            images = ldm(
-                [prompt],
-                num_inference_steps=STEPS,
-                eta=ETA,
-                guidance_scale=GUIDANCE_SCALE
-            )["sample"]
+            with torch.autocast("cuda"):
+                images = ldm(
+                    [prompt],
+                    num_inference_steps=STEPS,
+                    eta=ETA,
+                    guidance_scale=GUIDANCE_SCALE
+                )["sample"]
             result["images"].append(images[0])
             result["seeds"].append(seed)
         return result["images"], result["seeds"]