optimize(f0): move fcpe into rvc.f0

rvc/f0/crepe.py

@@ -16,6 +16,8 @@ class CRePE(F0Predictor):
         sampling_rate=44100,
         device="cpu",
     ):
+        if "privateuseone" in str(device):
+            device = "cpu"
         super().__init__(
             hop_length,
             f0_min,
@@ -32,11 +34,13 @@ class CRePE(F0Predictor):
     ):
         if p_len is None:
             p_len = wav.shape[0] // self.hop_length
+        if not torch.is_tensor(wav):
+            wav = torch.from_numpy(wav)
         # Pick a batch size that doesn't cause memory errors on your gpu
         batch_size = 512
         # Compute pitch using device 'device'
         f0, pd = torchcrepe.predict(
-            torch.tensor(np.copy(wav))[None].float().to(self.device),
+            wav.float().to(self.device).unsqueeze(dim=0),
             self.sampling_rate,
             self.hop_length,
             self.f0_min,