train demucs split with normalization

aicrowd.json

 {
-  "challenge_id": "evaluations-api-music-demixing",
-  "grader_id": "evaluations-api-music-demixing",
-  "authors": [
-    "yoyololicon"
-  ],
-  "description": "Demucs with separated decoders",
-  "external_dataset_used": true
+    "challenge_id": "evaluations-api-music-demixing",
+    "grader_id": "evaluations-api-music-demixing",
+    "authors": [
+        "yoyololicon"
+    ],
+    "description": "Demucs with separated decoders",
+    "external_dataset_used": false
 }
\ No newline at end of file

test_demucs.py

@@ -12,7 +12,7 @@ def separate(
     audio,
     rate,
     model,
-    shifts=1,
+    shifts=6,
     device="cpu"
 ):
 
@@ -41,6 +41,7 @@ def separate(
                 y += shifted_y[j, ..., start:start + valid_length]
         y /= shifts
 
+    y = y.clamp(-0.99, 0.99)
     return y.numpy()