def initiate():
IM_SIZE = 2 # 80
N_CHANEL = 9 # this is the representation of a block by 9 blocks
K = 6 # env.action_space.n
D = IM_SIZE * N_CHANEL
hidden_layer_sizes = [128, 64, 32]
gamma = 0.5
# number of random test
batch_sz = 32
count = 0
tf.reset_default_graph()
model = Dueling_DQN_PER_2D(D=D, K=K, batch_sz=batch_sz, hidden_layer_sizes=hidden_layer_sizes,
gamma=gamma, lr=2.3e-6, N_CHANEL=N_CHANEL, IM_SIZE=IM_SIZE, scope="DDQN")
print("DRL model loaded")
init = tf.global_variables_initializer()
sess = tf.InteractiveSession()
sess.run(init)
saver = tf.train.Saver()
MODEL_PATH = "../logs/2d/save_models/2d_mean_std"
saver.restore(sess, MODEL_PATH)
model.set_session(sess)
return model
D = IM_SIZE * N_CHANEL
hidden_layer_sizes = [128, 64, 32]
gamma = 0.5
starting_pixel_loc_list = [[20, 340], [320, 15]]
# number of random test
batch_sz = 32
count = 0
#tf.reset_default_graph()
model = Dueling_DQN_PER_2D(D=D,
K=K,
batch_sz=batch_sz,
hidden_layer_sizes=hidden_layer_sizes,
gamma=gamma,
lr=2.3e-6,
N_CHANEL=N_CHANEL,
IM_SIZE=IM_SIZE,
scope="DDQN")
init = tf.global_variables_initializer()
sess = tf.InteractiveSession()
sess.run(init)
saver = tf.train.Saver()
MODEL_PATH = "../logs/2d/save_models/2d_mean_std"
saver.restore(sess, MODEL_PATH)
model.set_session(sess)