first use of ema model.

.gitattributes

@@ -30,3 +30,4 @@ 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
+wavegru_vocoder_1024_v3_1340000.ckpt filter=lfs diff=lfs merge=lfs -text

app.py

@@ -15,7 +15,7 @@ def speak(text):
     )
 
     wavegru_config, wavegru_net = load_wavegru_net(
-        "./wavegru.yaml", "./wavegru_vocoder_1024_v3_1330000.ckpt"
+        "./wavegru.yaml", "./wavegru_vocoder_1024_v3_1340000.ckpt"
     )
 
     wave_cpp_weight_mask = extract_weight_mask(wavegru_net)

extract_model.py

@@ -1,5 +1,5 @@
 import pickle
 
-dic = pickle.load(open("./wavegru_vocoder_1024_v3_1330000.ckpt", "rb"))
+dic = pickle.load(open("./wavegru_vocoder_1024_v3_1340000.ckpt", "rb"))
 del dic["optim_state_dict"]
-pickle.dump(dic, open("./wavegru_vocoder_1024_v3_1330000.ckpt", "wb"))
+pickle.dump(dic, open("./wavegru_vocoder_1024_v3_1340000.ckpt", "wb"))

wavegru_vocoder_1024_v3_1330000.ckpt → wavegru_vocoder_1024_v3_1340000.ckpt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0806dc3002458f8468041db482757a21d362648ec1676e672306c20ee7507119
+oid sha256:32e253d4ac9e1b72ba18ab51134894eba0ac12d3595d10b93ed9362719b443f0
 size 69717674