Upload app.py

app.py

@@ -10,13 +10,13 @@ def fill(out: ti.types.ndarray(), value: ti.types.ndarray()):
     for I in ti.grouped(out):
         out[I] = value[None]
 
-out = torch.empty((10,), dtype=torch.int32)
-value = torch.tensor(2, dtype=torch.int32)  # torch scalar
+out = torch.empty((10,), dtype=torch.float16)
+value = torch.tensor(2, dtype=torch.float16)  # torch scalar
 fill(out, value)
 
 
 pipe = UnCLIPPipeline.from_pretrained("kakaobrain/karlo-v1-alpha", torch_dtype=torch.float16)
-pipe = pipe.to("cuda")
+pipe = pipe.to("cpu")
 
 @ti.func
 def run(prompt):