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Move back to tanh for frame rate network

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Swish has lower loss, but doesn't seem to improve quality
This commit is contained in:
Jean-Marc Valin 2022-09-24 03:19:26 -04:00
parent f5c251c5d5
commit d45ab6fcb6
1 changed files with 3 additions and 3 deletions
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6
dnn/training_tf2/lpcnet.py
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@ -241,14 +241,14 @@ def new_lpcnet_model(rnn_units1=384, rnn_units2=16, nb_used_features=20, batch_s
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: