def test_get_possible_bets(self):
node = Node()
node.current_player = constants.players.P1
node.street = 0
node.bets = arg.IntTensor([1, 1]).to(arg.device)
node.num_bets = 0
possible_bets = bet_sizing.get_possible_bets(node)
out = arg.IntTensor([3, 1]).to(arg.device)
torch.testing.assert_allclose(possible_bets, out)
node = Node()
node.current_player = constants.players.P1
node.street = 1
node.bets = arg.IntTensor([3, 5]).to(arg.device)
node.num_bets = 0
possible_bets = bet_sizing.get_possible_bets(node)
out = arg.IntTensor([9, 5]).to(arg.device)
torch.testing.assert_allclose(possible_bets, out)
node = Node()
node.current_player = constants.players.P1
node.street = 1
node.bets = arg.IntTensor([3, 5]).to(arg.device)
node.num_bets = 2
possible_bets = bet_sizing.get_possible_bets(node)
out = torch.empty([0, 2], dtype=arg.int_dtype).to(arg.device)
torch.testing.assert_allclose(possible_bets, out)
def test_board_to_street(self):
board = arg.IntTensor([]).to(arg.device)
street = card_tools.board_to_street(board)
self.assertEqual(street, 0)
board = arg.IntTensor([2]).to(arg.device)
street = card_tools.board_to_street(board)
self.assertEqual(street, 1)
def test_build_tree(self):
params = TreeParams()
params.root_node = Node()
params.root_node.board = card_to_string.string_to_cards('')
params.root_node.board_string = ''
params.root_node.street = 0
params.root_node.current_player = constants.players.P1
params.root_node.bets = arg.IntTensor([1, 1]).to(arg.device)
root = tree_builder.build_tree(params)
tree_visulizer.draw_tree(root)
def test_get_children_chance_nodes(self):
node = Node()
node.board_string = ''
node.board = card_to_string.string_to_cards(node.board_string)
node.street = 0
node.num_bets = 0
node.current_player = constants.players.P1
node.bets = arg.IntTensor([1, 1]).to(arg.device)
children = tree_builder.get_children_chance_nodes(node)
for child in children:
pass
def test_build_tree(self):
params = TreeParams()
params.root_node = Node()
params.root_node.board = card_to_string.string_to_cards('')
params.root_node.board_string = ''
params.root_node.street = 0
params.root_node.current_player = constants.players.P1
params.root_node.bets = arg.IntTensor([1, 1]).to(arg.device)
root = tree_builder.build_tree(params)
self.terminal_node = 0
self.chacne_node = 0
self.else_node = 0
self.dfs(root)
import context
import torch
from base import TreeParams, Node
from settings import arg, constants
from game import card_to_string, card_tools
from tree import tree_builder, TreeCFR, tree_visulizer, tree_strategy_sl
params = TreeParams()
params.root_node = Node()
params.root_node.board_string = arg.board_string
params.root_node.board = card_to_string.string_to_cards(arg.board_string)
params.root_node.street = arg.street
params.root_node.current_player = constants.players.P1
params.root_node.bets = arg.IntTensor([100, 100]).to(arg.device)
root = tree_builder.build_tree(params)
starting_range = torch.zeros([constants.players_count, constants.card_count],
dtype=arg.dtype).to(arg.device)
starting_range[0] = card_tools.get_uniform_range(params.root_node.board)
starting_range[1] = card_tools.get_uniform_range(params.root_node.board)
tree_cfr = TreeCFR()
tree_cfr.run_cfr(root, starting_range)
tree_visulizer.draw_tree(root)
tree_strategy_sl.save_strategy(root)
def test_get_second_round_boards(self):
boards = card_tools.get_second_round_boards()
out = arg.IntTensor([[0], [1], [2], [3], [4], [5]]).to(arg.device)
torch.testing.assert_allclose(boards, out)
def test_get_possible_hand_index(self):
board = arg.IntTensor([5]).to(arg.device)
possible_hand = card_tools.get_possible_hand_index(board)
out = arg.IntTensor([1, 1, 1, 1, 1, 0]).to(arg.device)
torch.testing.assert_allclose(possible_hand, out)
def test_get_hand_strength(self):
board = arg.IntTensor([5]).to(arg.device)
strength = card_tools.get_hand_strength(board)
out = arg.IntTensor([1, 1, 2, 2, 4, 4]).to(arg.device)
torch.testing.assert_allclose(strength, out)