use 4 shifts

test_demucs.py

@@ -12,14 +12,14 @@ def separate(
     audio,
     rate,
     model,
-    shifts=5,
+    shifts=4,
     device="cpu"
 ):
 
     # convert numpy audio to torch
     audio_torch = torch.tensor(audio.T).float().to(device)
     max_shift = int(rate * 0.5)
-    batch_size = 4
+    batch_size = 3
     valid_length = audio_torch.size(1)
     padded_length = valid_length + max_shift
     padded_audio = F.pad(audio_torch, [max_shift] * 2)