from network import Network
import tensorflow as tf
import random
import numpy as np


from board import Board

import main

config = main.config.copy()
config['model'] = "tesauro_blah"
config['force_creation'] = True
network = Network(config, config['model'])

session = tf.Session()

session.run(tf.global_variables_initializer())
network.restore_model(session)
initial_state = Board.initial_state

initial_state_1 = ( 0,
                    0, 0, 0, 2, 0, -5,
                    0, -3, 0, 0, 0, 0,
                    -5, 0, 0, 0, 3, 5,
                    0, 0, 0, 0, 5, -2,
                    0 )

initial_state_2 = ( 0,
                    -5, -5, -3, -2, 0, 0,
                    0, 0, 0, 0, 0, 0,
                    0, 0, 0, 15, 0, 0,
                    0, 0, 0, 0, 0, 0,
                    0 )

boards = {initial_state,
          initial_state_1,
          initial_state_2 }


print("-"*30)
print(network.do_ply(session, boards, 1))

print(" "*10 + "network_test")
print(" "*20 + "Depth 1")
print(network.n_ply(1, session, boards, 1))

print(" "*20 + "Depth 2")
print(network.n_ply(2, session, boards, 1))

# #print(x.shape)
# with graph_lol.as_default():
#     session_2 = tf.Session(graph = graph_lol)
#     network_2 = Network(session_2)
#     network_2.restore_model()
#     print(network_2.eval_state(initial_state))
    
# print(network.eval_state(initial_state))