new model

.gitattributes

@@ -29,3 +29,4 @@ bazelisk-linux-amd64 filter=lfs diff=lfs merge=lfs -text
 wavegru_mod.so filter=lfs diff=lfs merge=lfs -text
 pretrained_model_ljs_600k.ckpt filter=lfs diff=lfs merge=lfs -text
 wavegru_vocoder_1024_v3_1310000.ckpt filter=lfs diff=lfs merge=lfs -text
+wavegru_vocoder_1024_v3_1330000.ckpt filter=lfs diff=lfs merge=lfs -text

extract_model.py

@@ -1,5 +1,5 @@
 import pickle
 
-dic = pickle.load(open("./wavegru_vocoder_1024_v3_1310000.ckpt", "rb"))
+dic = pickle.load(open("./wavegru_vocoder_1024_v3_1330000.ckpt", "rb"))
 del dic["optim_state_dict"]
-pickle.dump(dic, open("./wavegru_vocoder_1024_v3_1310000.ckpt", "wb"))
+pickle.dump(dic, open("./wavegru_vocoder_1024_v3_1330000.ckpt", "wb"))

inference.py

@@ -67,7 +67,7 @@ def mel_to_wav(net, netcpp, mel, config):
     if len(mel.shape) == 2:
         mel = mel[None]
     pad = config["num_pad_frames"] // 2 + 2
-    mel = np.pad(mel, [(0, 0), (pad, pad), (0, 0)], mode="edge")
+    mel = np.pad(mel, [(0, 0), (pad, pad), (0, 0)], mode="reflect")
     ft = wavegru_inference(net, mel)
     ft = jax.device_get(ft[0])
     wav = netcpp.inference(ft, 1.0)

wavegru_vocoder_1024_v3_1310000.ckpt → wavegru_vocoder_1024_v3_1330000.ckpt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:daf1d772c67ebbe875429fe358429f37776e56139417058738253e0cbb787e06
+oid sha256:0806dc3002458f8468041db482757a21d362648ec1676e672306c20ee7507119
 size 69717674