diff --git a/tool/encoder_distance.py b/tool/encoder_distance.py
new file mode 100644
index 0000000..b6933ec
--- /dev/null
+++ b/tool/encoder_distance.py
@@ -0,0 +1,32 @@
+from pathlib import Path
+
+import torch
+#
+# data = {}
+#
+# for i in range(1, 422 + 1):
+#     _, names = torch.load(f"/tmp/pt/batch{i}.pt")
+#     generated = torch.load(f"/tmp/pt/generated{i}.pt")
+#     print(len(names))
+#     for j, n in enumerate(names):
+#         data[Path(names[j]).stem] = generated[j]
+#
+# torch.save(data, "/tmp/data.pt")
+
+data = torch.load("/tmp/data.pt")
+
+videos = sorted(list(set([k.split("@")[0] for k in data.keys()])))
+
+for idx in range(len(videos)):
+    print(videos[idx])
+    videos_data = {}
+    for k in data:
+        if k.startswith(videos[idx]):
+            videos_data[int(k.split("@")[-1])] = data[k]
+
+    to_save = []
+    for i in range(2, len(videos_data) + 1):
+        to_save.append(torch.mean(torch.abs(videos_data[i] - videos_data[1])).cpu())
+
+    torch.save(to_save, f"{videos[idx]}.pt")
+    print(f"{videos[idx]}.pt")
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