I tried teaching AI how to play breakout but my code crashes when I try to teach DQN model.
``
import gym
import numpy as np
import tensorflow as tf
from rl.agents.dqn import DQNAgent
from rl.policy import LinearAnnealedPolicy, EpsGreedyQPolicy
from rl.memory import SequentialMemory
from keras.layers import Dense, Flatten, Convolution2D

env = gym.make('ALE/Breakout-v5', render_mode='rgb_array')
height, width, channels = env.observation_space.shape
actions = env.action_space.n

episodes = 10
for episode in range(1, episodes + 1):
env.reset()
done = False
score = 0

def buildModel(height, width, channels, actions):
model = tf.keras.Sequential()
model.add(Convolution2D(32, (8, 8), strides=(4, 4), activation='relu', input_shape=(3,height, width, channels)))
model.add(Convolution2D(64, (4, 4), strides=(2, 2), activation='relu'))
model.add(Convolution2D(64, (3, 3), activation='relu'))
model.add(Flatten())
model.add(Dense(512, activation='relu'))
model.add(Dense(256, activation='relu'))
model.add(Dense(actions, activation='linear'))
return model

def buildAgent(model, actions):
policy = LinearAnnealedPolicy(EpsGreedyQPolicy(), attr='eps', value_max=1., value_min=.1, value_test=.2, nb_steps=10000)
memory = SequentialMemory(limit=1000, window_length=3)
dqn = DQNAgent(model=model, memory=memory, policy=policy,
enable_dueling_network=True, dueling_type='avg',
nb_actions=actions, nb_steps_warmup=1000)
return dqn

model = buildModel(height, width, channels, actions)

DQN = buildAgent(model, actions)
DQN.compile(tf.keras.optimizers.Adam(learning_rate=1e-4), metrics=['mae'])
DQN.fit(env, nb_steps=1000000, visualize=True, verbose=1)

scores = DQN.test(env, nb_episodes=1000, visualize=True)
print(np.mean(scores.history['episode_reward']))
``

Error: ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()