ref: d45ab6fcb6e8d61a354af1d96b3486c3c13f07b2
parent: f5c251c5d5faf08d15571b0ba7f34c3474a55fb8
author: Jean-Marc Valin <jmvalin@amazon.com>
date: Fri Sep 23 23:19:26 EDT 2022
Move back to tanh for frame rate network Swish has lower loss, but doesn't seem to improve quality
--- a/dnn/training_tf2/lpcnet.py
+++ b/dnn/training_tf2/lpcnet.py
@@ -241,14 +241,14 @@
dec_state2 = Input(shape=(rnn_units2,))
padding = 'valid' if training else 'same'
- fconv1 = Conv1D(cond_size, 3, padding=padding, activation='swish', name='feature_conv1')
- fconv2 = Conv1D(cond_size, 3, padding=padding, activation='swish', name='feature_conv2')
+ fconv1 = Conv1D(cond_size, 3, padding=padding, activation='tanh', name='feature_conv1')
+ fconv2 = Conv1D(cond_size, 3, padding=padding, activation='tanh', name='feature_conv2')
pembed = Embedding(256, 64, name='embed_pitch')
cat_feat = Concatenate()([feat, Reshape((-1, 64))(pembed(pitch))])
cfeat = fconv2(fconv1(cat_feat))
- fdense1 = Dense(cond_size, activation='swish', name='feature_dense1')
+ fdense1 = Dense(cond_size, activation='tanh', name='feature_dense1')
fdense2 = Dense(cond_size, activation='tanh', name='feature_dense2')
if flag_e2e and quantize:
--
⑨