checkpoint_dir ='64units-intended/2players_64hid_checkpoints'
for epoch in range(20):
# rl_dir2 = checkpoint_dir+'/rl_checkpoints/checkpoint_' + str(epoch+2) + '000.pt'
# sl_dir1 = checkpoint_dir+'/sl_checkpoints/checkpoint_' + str(epoch+1) + '000.pt'
# sl_dir2 = checkpoint_dir+'/sl_checkpoints/checkpoint_' + str(epoch+2) + '000.pt'
policy_net = {}
sl_net = {}
rl_dir = {}
sl_dir = {}
for i in range(num_NFSP):
rl_dir[i] = checkpoint_dir+'/rl_checkpoints/checkpoint_' + str(epoch+1+i) + '000.pt'
sl_dir[i] = checkpoint_dir+'/sl_checkpoints/checkpoint_' + str(epoch+1+i) + '000.pt'
policy_net[i] = DQN_limit(num_player=num_player,big=False, num_action = 3, hidden_units = hid).to(device)
sl_net[i] = MLP_limit(num_player=num_player, big=False, num_action = 3, hidden_units = hid).to(device)
checkpoint = torch.load(rl_dir[i], map_location='cpu')
policy_net[i].load_state_dict(checkpoint['model'])
policy_net[i].eval()
checkpoint = torch.load(sl_dir[i], map_location='cpu')
sl_net[i].load_state_dict(checkpoint['model'])
sl_net[i].eval()
results = []
for expriment in range(3):
game_board = {}
sum_board = {}
env = LimitTexasHoldemEnv(num_player, max_limit=1e9,
debug=False) #initialize 3-player game
env.add_player(0, stack=20000) # add a player to seat 0 with 2000 "chips"
env.add_player(1, stack=20000) # add a player to seat 1 with 2000 "chips"
env.add_player(2, stack=20000) # add a player to seat 2 with 2000 "chips"
env.add_player(3, stack=20000) # add a player to seat 2 with 2000 "chips"
card_dictionary = get_card_dict()
for epoch in range(num_versions):
rl_dir = checkpoint_dir + '/rl_checkpoints/checkpoint_' + str(epoch +
1) + '000.pt'
sl_dir = checkpoint_dir + '/sl_checkpoints/checkpoint_' + str(epoch +
1) + '000.pt'
# policy_net = DQN(num_player=num_player,big=False).to(device)
policy_net = DQN_limit(num_player=num_player,
big=big,
num_action=3,
hidden_units=hid).to(device)
# checkpoint = torch.load('../holdem_result/rl_checkpoints/checkpoint1999999_8235201.000.pt')
checkpoint = torch.load(rl_dir, map_location='cpu')
policy_net.load_state_dict(checkpoint['model'])
policy_net.eval()
sl_net = MLP_limit(num_player=num_player,
big=big,
num_action=3,
hidden_units=hid).to(device)
# sl_net = MLP(num_player=num_player, big=False).to(device)
checkpoint = torch.load(sl_dir, map_location='cpu')
# checkpoint = torch.load('../holdem_result/sl_checkpoints/checkpoint1999999_8235201.000.pt')
sl_net.load_state_dict(checkpoint['model'])
sl_net.eval()
# players
players = {}
for i in range(num_player):
players[i] = NFSPLimit(card_dict=card_dictionary, device=device)
# memory
M_sl = SLMemory(num_SL_memory)
M_rl = RLMemory(num_RL_memory)
# networks
# networks
policy_net = DQN_limit(num_player=num_player,
big=big,
res_net=use_res_net,
num_layer=num_layer,
num_action=3,
hidden_units=num_hid).to(device)
target_net = DQN_limit(num_player=num_player,
big=big,
res_net=use_res_net,
num_layer=num_layer,
num_action=3,
hidden_units=num_hid).to(device)
target_net.load_state_dict(policy_net.state_dict())
target_net.eval()
sl_net = MLP_limit(num_player=num_player,
big=big,
res_net=use_res_net,
num_layer=num_layer,
num_action=3,