lczerolens.play.puzzle#

Preproces functions for chess puzzles.

Attributes#

PUZZLE_DATASET_FEATURES

Classes#

Puzzle

Module Contents#

lczerolens.play.puzzle.PUZZLE_DATASET_FEATURES[source]#
class lczerolens.play.puzzle.Puzzle[source]#
puzzle_id: str[source]#
fen: str[source]#
initial_move: chess.Move[source]#
moves: List[chess.Move][source]#
rating: int[source]#
rating_deviation: int[source]#
popularity: int[source]#
nb_plays: int[source]#
themes: List[str][source]#
game_url: str[source]#
opening_tags: List[str][source]#
classmethod from_dict(obj)[source]#
Parameters:

obj (Dict[str, Union[str, int, None]])

Return type:

Puzzle

__len__()[source]#
Return type:

int

property initial_board: lczerolens.board.LczeroBoard[source]#
Return type:

lczerolens.board.LczeroBoard

board_move_generator(all_moves=False)[source]#
Parameters:

all_moves (bool)

Return type:

Iterable[Tuple[lczerolens.board.LczeroBoard, chess.Move]]

classmethod evaluate_multiple(puzzles, sampler, all_moves=False, compute_metrics=True, **kwargs)[source]#
Parameters:
Return type:

Union[Iterable[Dict[str, float]], Iterable[Tuple[torch.Tensor, torch.Tensor, chess.Move]]]

evaluate(sampler, all_moves=False, **kwargs)[source]#
Parameters:
Return type:

Tuple[float, Optional[float]]

static compute_metrics(puzzles, inputs, all_moves=False)[source]#
Parameters:

  • puzzles (Iterable[Puzzle])

  • inputs (Iterable[Tuple[torch.Tensor, torch.Tensor, chess.Move]])

  • all_moves (bool)

Return type:

Iterable[Dict[str, float]]

_repr_svg_()[source]#
Return type:

str