Attempt to infer V2 models (#927)

infer_cli.py

@@ -1,13 +1,26 @@
-import os, sys, pdb, torch
+from scipy.io import wavfile
+from fairseq import checkpoint_utils
+from lib.audio import load_audio
+from lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+from vc_infer_pipeline import VC
+from multiprocessing import cpu_count
+import numpy as np
+import torch
+import sys
+import glob
+import argparse
+import os
+import sys
+import pdb
+import torch
 
 now_dir = os.getcwd()
 sys.path.append(now_dir)
-import argparse
-import glob
-import sys
-import torch
-import numpy as np
-from multiprocessing import cpu_count
 
 ####
 # USAGE
@@ -119,11 +132,6 @@ class Config:
 config = Config(device, is_half)
 now_dir = os.getcwd()
 sys.path.append(now_dir)
-from vc_infer_pipeline import VC
-from infer_pack.models import SynthesizerTrnMs256NSFsid, SynthesizerTrnMs256NSFsid_nono
-from my_utils import load_audio
-from fairseq import checkpoint_utils
-from scipy.io import wavfile
 
 hubert_model = None
 
@@ -224,10 +232,20 @@ def get_vc(model_path):
     cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
     if_f0 = cpt.get("f0", 1)
     version = cpt.get("version", "v1")
-    if if_f0 == 1:
-        net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=is_half)
-    else:
-        net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+    if version == "v1":
+        if if_f0 == 1:
+            net_g = SynthesizerTrnMs256NSFsid(
+                *cpt["config"], is_half=is_half
+            )
+        else:
+            net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+    elif version == "v2":
+        if if_f0 == 1:
+            net_g = SynthesizerTrnMs768NSFsid(
+                *cpt["config"], is_half=is_half
+            )
+        else:
+            net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
     del net_g.enc_q
     print(net_g.load_state_dict(cpt["weight"], strict=False))
     net_g.eval().to(device)