new model

.gitattributes

@@ -26,6 +26,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 bazelisk-linux-amd64 filter=lfs diff=lfs merge=lfs -text
-wavegru.ckpt 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

app.py

@@ -14,7 +14,7 @@ alphabet, tacotron_net, tacotron_config = load_tacotron_model(
 )
 
 
-wavegru_config, wavegru_net = load_wavegru_net("./wavegru.yaml", "./wavegru.ckpt")
+wavegru_config, wavegru_net = load_wavegru_net("./wavegru.yaml", "./wavegru_vocoder_1024_v3_1310000.ckpt")
 
 wave_cpp_weight_mask = extract_weight_mask(wavegru_net)
 wavecpp = load_wavegru_cpp(wave_cpp_weight_mask, wavegru_config["upsample_factors"][-1])

extract_model.py

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