import keras;
import numpy as np;

model = keras.models.Sequential();

model.add(keras.layers.LSTM(7, input_shape=(5, 1), stateful=True, batch_size=6, name="input"));
model.add(keras.layers.Dense(4, activation="relu", name="hidden1"));
model.add(keras.layers.Dense(2, activation="softmax", name="output"));
model.compile(optimizer="rmsprop", loss="binary_crossentropy", metrics=["accuracy"]);

keras.utils.plot_model(model, show_shapes=True);
model.save("model.h5");