keras dosen't load the model and weights when using checkpoint

Question

I'm using keras to build a deep autoencoder. I used its checkpointer to load the model and the weights but the result is always None which I think it means that the checkpoint dosen't work correctly and is not saving weights. Here is the code how I proceed:

checkpointer = ModelCheckpoint(filepath="weights.best.h5",
                               verbose=0,
                               save_best_only=True)
tensorboard = TensorBoard(log_dir='/tmp/autoencoder',
                          histogram_freq=0,
                          write_graph=True,
                          write_images=True)
input_enc = Input(shape=(input_size,))
hidden_1 = Dense(hidden_size1, activation='relu')(input_enc)
hidden_11 = Dense(hidden_size2, activation='relu')(hidden_1)
code = Dense(code_size, activation='relu')(hidden_11)
hidden_22 = Dense(hidden_size2, activation='relu')(code)
hidden_2 = Dense(hidden_size1, activation='relu')(hidden_22)
output_enc = Dense(input_size, activation='tanh')(hidden_2)
autoencoder_yes = Model(input_enc, output_enc)

autoencoder_yes.compile(optimizer='adam',
                         loss='mean_squared_error', 
                         metrics=['accuracy'])
history_yes = autoencoder_yes.fit(df_noyau_norm_y, df_noyau_norm_y,
                               epochs=200,
                                batch_size=batch_size,
                                shuffle = True,
                                validation_data=(df_test_norm_y, df_test_norm_y),
                                verbose=1, 
                                callbacks=[checkpointer, tensorboard]).history

autoencoder_yes.save_weights("weights.best.h5")
print(autoencoder_yes.load_weights("weights.best.h5"))

Can somebody help me find out a way to resolve the problem? Thanks

Answer 1

No, your interpretation of load_weights returning None is not correct. Load weights is a procedure, it does not return anything, and if you assign the return value of a procedure to a variable, it will get the value of None.

So weight saving is probably working fine, its just your interpretation that is wrong.

Answer 2

you should use save_weights_only=True. Without this the whole model is saved not just the weights. To be able to load weights you must save weights like this:

checkpointer = ModelCheckpoint(filepath="weights.best.h5",
                           verbose=0, save_weights_only=True,
                           save_best_only=True)