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training

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This commit is contained in:
Jean-Marc Valin 2019-04-11 11:06:37 -04:00
parent 9b8d72ea87
commit 60790784a4
1 changed files with 2 additions and 1 deletions
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3
dnn/train_lpcnet.py
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@ -103,7 +103,7 @@ del pred
del in_exc del in_exc
# dump models to disk as we go # dump models to disk as we go
checkpoint = ModelCheckpoint('lpcnet24g_384_10_G16_{epoch:02d}.h5') checkpoint = ModelCheckpoint('lpcnet30_384_10_G16_{epoch:02d}.h5')
#Set this to True to adapt an existing model (e.g. on new data) #Set this to True to adapt an existing model (e.g. on new data)
adaptation = False adaptation = False
@ -121,4 +121,5 @@ else:
decay = 5e-5 decay = 5e-5
model.compile(optimizer=Adam(lr, amsgrad=True, decay=decay), loss='sparse_categorical_crossentropy') model.compile(optimizer=Adam(lr, amsgrad=True, decay=decay), loss='sparse_categorical_crossentropy')
model.save_weights('lpcnet30_384_10_G16_00.h5');
model.fit([in_data, features, periods], out_exc, batch_size=batch_size, epochs=nb_epochs, validation_split=0.0, callbacks=[checkpoint, sparsify]) model.fit([in_data, features, periods], out_exc, batch_size=batch_size, epochs=nb_epochs, validation_split=0.0, callbacks=[checkpoint, sparsify])