def test_loaded_dataset_white_move(self):
s_idcs_val, x_val, yv_val, yp_val, pgn_datasets_val = load_pgn_dataset(
dataset_type='test',
part_id=0,
print_statistics=True,
print_parameters=True,
normalize=True)
board = chess.variant.CrazyhouseBoard()
mv_converted = policy_to_move(yp_val[0], is_white_to_move=True)
mv_converted_is_legal = False
# check if the move is legal in the starting position
for mv in board.legal_moves:
if mv == mv_converted:
mv_converted_is_legal = True
self.assertTrue(
mv_converted_is_legal,
msg=
'Convert move %s is not a legal move in the starting position for WHITE'
% mv_converted.uci())
def test_loaded_dataset_black_move(self):
"""
Loads the dataset file and checks the first move policy vector for black for correctness
:return:
"""
s_idcs_val, x_val, yv_val, yp_val, pgn_datasets_val = load_pgn_dataset(
dataset_type='test',
part_id=0,
print_statistics=True,
print_parameters=True,
normalize=True)
board = chess.variant.CrazyhouseBoard()
# push a dummy move
board.push_uci('e2e4')
mv_conv0 = policy_to_move(yp_val[1], is_white_to_move=False)
mv_conv1, prob = policy_to_best_move(board, yp_val[1])
self.assertEqual(prob,
1,
msg='The policy vector has to be one hot encoded.')
selected_moves, move_probabilites = policy_to_moves(board, yp_val[1])
mv_conv2 = selected_moves[0]
self.assertGreater(move_probabilites[0],
0,
msg='The move probability must be greater 0')
self.assertEqual(move_probabilites[0],
1,
msg='The policy vector has to be one hot encoded.')
converted_moves = [mv_conv0, mv_conv1, mv_conv2]
for mv_converted in converted_moves:
mv_converted_is_legal = False
# check if the move is legal in the starting position
for mv in board.legal_moves:
if mv == mv_converted:
mv_converted_is_legal = True
self.assertTrue(
mv_converted_is_legal,
msg=
'Convert move %s is not a legal move in the starting position for BLACK'
% mv_converted.uci())