AIP0-model_basic.py

import tensorflow as tf
import pickle
import numpy as np

class RLModel:
    def __init__(self, version = None, learning_rate = 1e-3):
        if version is not None:
            self.retrieveVariables(version)
        else:
            self.learning_rate = learning_rate
            self.create_model(nodes)
        
    def create_model(self):
        self.model = tf.keras.Sequential([
tf.keras.layers.Input((4 * 4 * 3,)),
tf.keras.layers.Dense(16, activation='relu'),
tf.keras.layers.Dense(4)
])
        self.model.compile(loss='mse', optimizer=tf.optimizers.Adam(self.learning_rate))

    def predict(self, board):
        return self.model.predict(np.array(board).reshape(1, -1))

    def retrieveVariables(self, version):
        self.model = tf.keras.models.load_model('{}.h5'.format(version))

    def saveVariables(self):
        self.model.save('newModel.h5')