Multistep for the stateful RNN (Keras)

steps_ahead = 5 # how much steps ahead to predict
dim = 1 # dimension of the input series

X_multi = X # copy input sequence to the separate variable in order not to add garbage to the original sequence

for i in range(0, steps_ahead):
    predicted = model_train_dict['model'].predict(X_multi, batch_size=batch_size)
    X_multi = np.append(X_multi, np.reshape(predicted[-1:], (1, 1, dim)), axis=0)