import tensorflow as tf
 
class Model:
    def __init__(self):
        self.model = tf.keras.Sequential()
        self.model.add(tf.keras.layers.Dense(32, input_shape=(784,), activation='relu'))
        self.model.add(tf.keras.layers.Dense(10, activation='softmax'))
        self.model.compile(optimizer='adam',
              loss='categorical_crossentropy',
              metrics=['accuracy'])
 
    def train(self, x_train, y_train, x_test, y_test):
        self.model.fit(x_train, y_train, epochs=5, validation_data=(x_test, y_test))
 
    def predict(self, x_predict):
        return self.model.predict(x_predict)
 

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