add

app.py

@@ -267,7 +267,7 @@ class BaseTrainer(object):
             for its, batch_data in enumerate(self.test_loader):
                 # loaded_data = self._load_data(batch_data)    
                 # net_out = self._g_test(loaded_data)
-                net_out = _warp(self.args,self.model, batch_data,self.joints,self.joint_mask_upper,self.joint_mask_hands,self.joint_mask_lower,self.use_trans,self.diffusion)
+                net_out = _warp(self.args,self.model, batch_data,self.joints,self.joint_mask_upper,self.joint_mask_hands,self.joint_mask_lower,self.use_trans)
                 tar_pose = net_out['tar_pose']
                 rec_pose = net_out['rec_pose']
                 tar_exps = net_out['tar_exps']
@@ -334,7 +334,8 @@ class BaseTrainer(object):
 
 
 @spaces.GPU(duration=149)
-def _warp(args,model, batch_data,joints,joint_mask_upper,joint_mask_hands,joint_mask_lower,use_trans,diffusion):
+def _warp(args,model, batch_data,joints,joint_mask_upper,joint_mask_hands,joint_mask_lower,use_trans):
+    diffusion = create_gaussian_diffusion(use_ddim=args.use_ddim)
     args,model,vq_model_upper,vq_model_hands,vq_model_lower,mean_upper,mean_hands,mean_lower,std_upper,std_hands,std_lower,trans_mean,trans_std,vqvae_latent_scale=_warp_create_cuda_model(args,model)