Update model.py

model.py

@@ -1100,7 +1100,7 @@ class StreamMultiDiffusion(nn.Module):
                 self.stock_noise,
                 torch.tensor(self.sub_timesteps_tensor, device=self.device),
             )
-            print('111111111111111111111', bootstrap_steps)
+            print('111111111111111111111', self.bootstrap_steps)
 
             x_t_latent = rearrange(x_t_latent, '(t p) c h w -> p t c h w', p=p)
             bootstrap_mask = (
@@ -1109,9 +1109,11 @@ class StreamMultiDiffusion(nn.Module):
             ) # (p, t, c, h, w)
             x_t_latent = (1.0 - bootstrap_mask) * bootstrap_latent[None] + bootstrap_mask * x_t_latent
             x_t_latent = rearrange(x_t_latent, 'p t c h w -> (t p) c h w')
+            print('222222222222222222222')
 
             # Centering.
             x_t_latent = shift_to_mask_bbox_center(x_t_latent, rearrange(self.masks, 'p t c h w -> (t p) c h w'), reverse=True)
+        print('333333333333333333333')
 
         t_list = self.sub_timesteps_tensor_  # (T * p,)
         if self.guidance_scale > 1.0 and self.cfg_type == 'initialize':