Update model.py

model.py

@@ -143,12 +143,12 @@ class StreamMultiDiffusion(nn.Module):
         self.pipe = load_model(model_key, self.sd_version, self.device, self.dtype).to(dtype=self.dtype)
 
         self.pipe.load_lora_weights(lora_key, weight_name=lora_weight_name, adapter_name='lcm')
-        self.pipe.fuse_lora(
-            fuse_unet=True,
-            fuse_text_encoder=True,
-            lora_scale=1.0,
-            safe_fusing=False,
-        )
+        # self.pipe.fuse_lora(
+        #     fuse_unet=True,
+        #     fuse_text_encoder=True,
+        #     lora_scale=1.0,
+        #     safe_fusing=False,
+        # )
         self.pipe.to(device=self.device, dtype=self.dtype)
         if use_xformers:
             self.pipe.enable_xformers_memory_efficient_attention()
@@ -1098,7 +1098,7 @@ class StreamMultiDiffusion(nn.Module):
             bootstrap_latent = self.scheduler.add_noise(
                 self.bootstrap_latent,
                 self.stock_noise,
-                torch.tensor(self.sub_timesteps_tensor, device=self.device),
+                self.sub_timesteps_tensor.clone().detach().to(self.device),
             )
 
             x_t_latent = rearrange(x_t_latent, '(t p) c h w -> p t c h w', p=p)