Cleanup

Remove the metric because it wasn't too useful and it's buggy in
Keras 2.2.4.

dnn/train_lpcnet.py

@@ -97,8 +97,8 @@ del sig
 del pred
 
 # dump models to disk as we go
-checkpoint = ModelCheckpoint('lpcnet18_384_10_G16_{epoch:02d}.h5')
+checkpoint = ModelCheckpoint('lpcnet20_384_10_G16_{epoch:02d}.h5')
 
-model.load_weights('lpcnet9b_384_10_G16_01.h5')
-model.compile(optimizer=Adam(0.001, amsgrad=True, decay=5e-5), loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
+#model.load_weights('lpcnet9b_384_10_G16_01.h5')
+model.compile(optimizer=Adam(0.001, amsgrad=True, decay=5e-5), loss='sparse_categorical_crossentropy')
 model.fit([in_data, in_exc, features, periods], out_exc, batch_size=batch_size, epochs=nb_epochs, validation_split=0.0, callbacks=[checkpoint, lpcnet.Sparsify(2000, 40000, 400, (0.05, 0.05, 0.2))])