Update app.py

app.py

@@ -279,10 +279,10 @@ def timestep_embedding(t: Tensor, dim, max_period=10000, time_factor: float = 10
     half = dim // 2
     
     # Do not block CUDA steam, but having about 1e-4 differences with Flux official codes:
-    freqs = torch.exp(-math.log(max_period) * torch.arange(start=0, end=half, dtype=torch.float32, device=t.device) / half)
+    # freqs = torch.exp(-math.log(max_period) * torch.arange(start=0, end=half, dtype=torch.float32, device=t.device) / half)
 
     # Block CUDA steam, but consistent with official codes:
-    # freqs = torch.exp(-math.log(max_period) * torch.arange(start=0, end=half, dtype=torch.float32) / half).to(t.device)
+    freqs = torch.exp(-math.log(max_period) * torch.arange(start=0, end=half, dtype=torch.float32) / half).to(t.device)
 
     args = t[:, None].float() * freqs[None]
     embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1)