diff --git a/mmedit/evaluation/metrics/ppl.py b/mmedit/evaluation/metrics/ppl.py
index ba6500de3a..7e22ef1ec3 100644
--- a/mmedit/evaluation/metrics/ppl.py
+++ b/mmedit/evaluation/metrics/ppl.py
@@ -240,6 +240,7 @@ def __next__(self):
                 if self.idx >= len(self.batch_sizes):
                     raise StopIteration
                 batch = self.batch_sizes[self.idx]
+                injected_noise = self.generator.make_injected_noise()
                 inputs = torch.randn([batch * 2, self.latent_dim],
                                      device=self.device)
                 if self.sampling == 'full':
@@ -270,6 +271,7 @@ def __next__(self):
                     inputs=dict(
                         noise=latent_e,
                         sample_kwargs=dict(
+                            injected_noise=injected_noise,
                             input_is_latent=(self.space == 'W'))))
 
         ppl_sampler = PPLSampler(
diff --git a/mmedit/utils/io_utils.py b/mmedit/utils/io_utils.py
index de965c1908..bd6128f707 100644
--- a/mmedit/utils/io_utils.py
+++ b/mmedit/utils/io_utils.py
@@ -3,7 +3,7 @@
 import os
 
 import click
-import mmcv
+import mmengine
 import requests
 import torch.distributed as dist
 from mmengine.dist import get_dist_info
@@ -67,7 +67,7 @@ def download_from_url(url,
     if rank == 0:
         # mkdir
         _dir = os.path.dirname(dest_path)
-        mmcv.mkdir_or_exist(_dir)
+        mmengine.mkdir_or_exist(_dir)
 
         if hash_prefix is not None:
             sha256 = hashlib.sha256()