def test_pick_moves(self):
player = initialize_basic_player()
root = player.root
root.child_N[coords.flatten_coords((2, 0))] = 10
root.child_N[coords.flatten_coords((1, 0))] = 5
root.child_N[coords.flatten_coords((3, 0))] = 1
root.position.n = go.N ** 2 # move 81, or 361, or... Endgame.
# Assert we're picking deterministically
self.assertTrue(root.position.n > player.temp_threshold)
move = player.pick_move()
self.assertEqual(move, (2, 0))
# But if we're in the early part of the game, pick randomly
root.position.n = 3
self.assertFalse(player.root.position.n > player.temp_threshold)
with mock.patch('random.random', lambda: .5):
move = player.pick_move()
self.assertEqual(move, (2, 0))
with mock.patch('random.random', lambda: .99):
move = player.pick_move()
self.assertEqual(move, (3, 0))
def test_pick_moves(self):
player = initialize_basic_player()
root = player.root
root.child_N[coords.flatten_coords((2, 0))] = 10
root.child_N[coords.flatten_coords((1, 0))] = 5
root.child_N[coords.flatten_coords((3, 0))] = 1
root.position.n = go.N ** 2 # move 81, or 361, or... Endgame.
# Assert we're picking deterministically
self.assertTrue(root.position.n > player.temp_threshold)
move = player.pick_move()
self.assertEqual(move, (2, 0))
# But if we're in the early part of the game, pick randomly
root.position.n = 3
self.assertFalse(player.root.position.n > player.temp_threshold)
with mock.patch('random.random', lambda: .5):
move = player.pick_move()
self.assertEqual(move, (2, 0))
with mock.patch('random.random', lambda: .99):
move = player.pick_move()
self.assertEqual(move, (3, 0))
def test_flatten(self):
self.assertEqual(coords.flatten_coords((0, 0)), 0)
self.assertEqual(coords.flatten_coords((0, 3)), 3)
self.assertEqual(coords.flatten_coords((3, 0)), 27)
self.assertEqual(coords.unflatten_coords(27), (3, 0))
self.assertEqual(coords.unflatten_coords(10), (1, 1))
self.assertEqual(coords.unflatten_coords(80), (8, 8))
self.assertEqual(coords.flatten_coords(coords.unflatten_coords(10)),
10)
self.assertEqual(
coords.unflatten_coords(coords.flatten_coords((5, 4))), (5, 4))
def test_do_not_explore_past_finish(self):
probs = np.array([0.02] * (go.N * go.N + 1), dtype=np.float32)
root = MCTSNode(go.Position())
root.select_leaf().incorporate_results(probs, 0, root)
first_pass = root.maybe_add_child(coords.flatten_coords(None))
first_pass.incorporate_results(probs, 0, root)
second_pass = first_pass.maybe_add_child(coords.flatten_coords(None))
with self.assertRaises(AssertionError):
second_pass.incorporate_results(probs, 0, root)
node_to_explore = second_pass.select_leaf()
# should just stop exploring at the end position.
self.assertEqual(node_to_explore, second_pass)
def test_pass(self):
self.assertEqual(coords.parse_sgf_coords(''), None)
self.assertEqual(coords.unflatten_coords(81), None)
self.assertEqual(coords.parse_kgs_coords('pass'), None)
self.assertEqual(coords.parse_pygtp_coords((0, 0)), None)
self.assertEqual(coords.unparse_sgf_coords(None), '')
self.assertEqual(coords.flatten_coords(None), 81)
self.assertEqual(coords.to_human_coord(None), 'pass')
self.assertEqual(coords.unparse_pygtp_coords(None), (0, 0))
def test_topleft(self):
self.assertEqual(coords.parse_sgf_coords('ia'), (0, 8))
self.assertEqual(coords.unflatten_coords(8), (0, 8))
self.assertEqual(coords.parse_kgs_coords('J9'), (0, 8))
self.assertEqual(coords.parse_pygtp_coords((9, 9)), (0, 8))
self.assertEqual(coords.unparse_sgf_coords((0, 8)), 'ia')
self.assertEqual(coords.flatten_coords((0, 8)), 8)
self.assertEqual(coords.to_human_coord((0, 8)), 'J9')
self.assertEqual(coords.unparse_pygtp_coords((0, 8)), (9, 9))
def test_upperleft(self):
self.assertEqual(coords.parse_sgf_coords('aa'), (0, 0))
self.assertEqual(coords.unflatten_coords(0), (0, 0))
self.assertEqual(coords.parse_kgs_coords('A9'), (0, 0))
self.assertEqual(coords.parse_pygtp_coords((1, 9)), (0, 0))
self.assertEqual(coords.unparse_sgf_coords((0, 0)), 'aa')
self.assertEqual(coords.flatten_coords((0, 0)), 0)
self.assertEqual(coords.to_human_coord((0, 0)), 'A9')
self.assertEqual(coords.unparse_pygtp_coords((0, 0)), (1, 9))
def test_make_dataset_from_sgf(self):
with tempfile.NamedTemporaryFile() as sgf_file, \
tempfile.NamedTemporaryFile() as record_file:
sgf_file.write(TEST_SGF.encode('utf8'))
sgf_file.seek(0)
preprocessing.make_dataset_from_sgf(sgf_file.name,
record_file.name)
recovered_data = self.extract_data(record_file.name)
start_pos = go.Position()
first_move = coords.parse_sgf_coords('fd')
next_pos = start_pos.play_move(first_move)
second_move = coords.parse_sgf_coords('cf')
expected_data = [
(features.extract_features(start_pos),
preprocessing._one_hot(coords.flatten_coords(first_move)), -1),
(features.extract_features(next_pos),
preprocessing._one_hot(coords.flatten_coords(second_move)), -1)
]
self.assertEqualData(expected_data, recovered_data)
def play_move(self, c):
'''
Notable side effects:
- finalizes the probability distribution according to
this roots visit counts into the class' running tally, `searches`
- Makes the node associated with this move the root, for future
`inject_noise` calls.
'''
if not self.two_player_mode:
self.searches_pi.append(
self.root.children_as_pi(self.root.position.n > self.temp_threshold))
self.qs.append(self.root.Q) # Save our resulting Q.
self.comments.append(self.root.describe())
self.root = self.root.maybe_add_child(coords.flatten_coords(c))
self.position = self.root.position # for showboard
del self.root.parent.children
return True # GTP requires positive result.
def play_move(self, c):
'''
Notable side effects:
- finalizes the probability distribution according to
this roots visit counts into the class' running tally, `searches_pi`
- Makes the node associated with this move the root, for future
`inject_noise` calls.
'''
if not self.two_player_mode:
self.searches_pi.append(
self.root.children_as_pi(self.root.position.n < self.temp_threshold))
self.qs.append(self.root.Q) # Save our resulting Q.
self.comments.append(self.root.describe())
self.root = self.root.maybe_add_child(coords.flatten_coords(c))
self.position = self.root.position # for showboard
del self.root.parent.children
return True # GTP requires positive result.
def _make_tf_example_from_pwc(position_w_context):
features = features_lib.extract_features(position_w_context.position)
pi = _one_hot(coords.flatten_coords(position_w_context.next_move))
value = position_w_context.result
return make_tf_example(features, pi, value)
def _make_tf_example_from_pwc(position_w_context):
features = features_lib.extract_features(position_w_context.position)
pi = _one_hot(coords.flatten_coords(position_w_context.next_move))
value = position_w_context.result
return make_tf_example(features, pi, value)
