diff --git a/ldm/models/diffusion/ddim.py b/ldm/models/diffusion/ddim.py
index c6cfd57..5087da4 100644
--- a/ldm/models/diffusion/ddim.py
+++ b/ldm/models/diffusion/ddim.py
@@ -266,11 +266,18 @@ class DDIMSampler(object):
             alphas_next = self.ddim_alphas[:num_steps]
             alphas = torch.tensor(self.ddim_alphas_prev[:num_steps])
 
+        timesteps = np.arange(self.ddpm_num_timesteps) if use_original_steps else self.ddim_timesteps
+        timesteps = timesteps[:num_steps]
+
+        total_steps = timesteps.shape[0]
+        iterator = tqdm(timesteps, desc='Encoding image', total=total_steps)
+
         x_next = x0
         intermediates = []
         inter_steps = []
-        for i in tqdm(range(num_steps), desc='Encoding Image'):
-            t = torch.full((x0.shape[0],), i, device=self.model.device, dtype=torch.long)
+        for i, step in enumerate(iterator):
+
+            t = torch.full((x0.shape[0],), step, device=self.model.device, dtype=torch.long)
             if unconditional_guidance_scale == 1.:
                 noise_pred = self.model.apply_model(x_next, t, c)
             else: