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training
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1 changed files with 2 additions and 1 deletions
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@ -103,7 +103,7 @@ del pred
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del in_exc
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# dump models to disk as we go
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checkpoint = ModelCheckpoint('lpcnet24g_384_10_G16_{epoch:02d}.h5')
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checkpoint = ModelCheckpoint('lpcnet30_384_10_G16_{epoch:02d}.h5')
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#Set this to True to adapt an existing model (e.g. on new data)
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adaptation = False
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@ -121,4 +121,5 @@ else:
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decay = 5e-5
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model.compile(optimizer=Adam(lr, amsgrad=True, decay=decay), loss='sparse_categorical_crossentropy')
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model.save_weights('lpcnet30_384_10_G16_00.h5');
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model.fit([in_data, features, periods], out_exc, batch_size=batch_size, epochs=nb_epochs, validation_split=0.0, callbacks=[checkpoint, sparsify])
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