Set Weights LSTM

lstm-setweights.py

embedding_dim = 100
optimizer = best_params['optimizer']

model = Sequential()
model.add(layers.Embedding(input_dim=vocab_size, 
                        output_dim=embedding_dim,
                        input_length=maxlen))
model.add(SpatialDropout1D(0.4))
model.add(LSTM(64, activation="tanh"))
model.add(Dense(3,activation='softmax'))
model.compile(optimizer=optimizer,
              loss='categorical_crossentropy',
              metrics=['accuracy'])

best_model_weights = study.user_attrs['best_model_weights']
# setting the saved weights to new model
model.set_weights(best_model_weights)

# evaluating on the test set
test_acc = model.evaluate(X_test,y_test)[1]
print(test_acc)