File size: 7,321 Bytes
3495881
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
"""
Board and move encoding for TinyChess.

Design notes
------------
* Positions are *canonicalised* to side-to-move = White by vertically mirroring
  the board and swapping piece colours when Black is to move. This is a
  lossless symmetry of chess (ignoring nothing: castling rights and en-passant
  are mirrored too), and it is a standard, non-cheating canonicalisation.
* A move is packed into a single int32 with structural fields only. We
  deliberately store *rules-derived* structure (from/to/promo/piece/capture/
  castle/ep) and no heuristic evaluation.
* Per-square features are kept separate (64 vectors); nothing is collapsed to a
  single vector at encoding time.
"""
from __future__ import annotations

import numpy as np
import chess

# ---------------------------------------------------------------------------
# Move packing
# ---------------------------------------------------------------------------
# bits: from(6) | to(6) | promo(3) | piece(3) | capture(1) | castle(1) | ep(1)
_F_FROM = 0
_F_TO = 6
_F_PROMO = 12
_F_PIECE = 15
_F_CAP = 18
_F_CASTLE = 19
_F_EP = 20

PROMO_CODES = {None: 0, chess.KNIGHT: 1, chess.BISHOP: 2, chess.ROOK: 3, chess.QUEEN: 4}
PROMO_INV = {v: k for k, v in PROMO_CODES.items()}
N_PROMO = 5
N_PIECE_TYPES = 6  # pawn..king -> 0..5

MOVE_FIELD_SIZES = dict(from_sq=64, to_sq=64, promo=N_PROMO, piece=N_PIECE_TYPES,
                        capture=2, castle=2, ep=2)


def pack_move(board: chess.Board, move: chess.Move) -> int:
    """Pack a legal move on `board` into an int32 of structural fields."""
    piece = board.piece_at(move.from_square)
    ptype = (piece.piece_type - 1) if piece is not None else 0
    is_ep = board.is_en_passant(move)
    is_cap = board.is_capture(move)
    is_castle = board.is_castling(move)
    v = (move.from_square << _F_FROM) | (move.to_square << _F_TO)
    v |= PROMO_CODES.get(move.promotion, 0) << _F_PROMO
    v |= ptype << _F_PIECE
    v |= int(is_cap) << _F_CAP
    v |= int(is_castle) << _F_CASTLE
    v |= int(is_ep) << _F_EP
    return v


def unpack_move(v: int) -> dict:
    return dict(
        from_sq=(v >> _F_FROM) & 63,
        to_sq=(v >> _F_TO) & 63,
        promo=(v >> _F_PROMO) & 7,
        piece=(v >> _F_PIECE) & 7,
        capture=(v >> _F_CAP) & 1,
        castle=(v >> _F_CASTLE) & 1,
        ep=(v >> _F_EP) & 1,
    )


def unpack_fields(v: np.ndarray) -> np.ndarray:
    """Vectorised unpack -> int64 array [..., 7] in MOVE_FIELD order."""
    v = np.asarray(v, dtype=np.int64)
    return np.stack([
        (v >> _F_FROM) & 63,
        (v >> _F_TO) & 63,
        (v >> _F_PROMO) & 7,
        (v >> _F_PIECE) & 7,
        (v >> _F_CAP) & 1,
        (v >> _F_CASTLE) & 1,
        (v >> _F_EP) & 1,
    ], axis=-1)


MOVE_FIELD_ORDER = ["from_sq", "to_sq", "promo", "piece", "capture", "castle", "ep"]


def packed_to_uci(v: int) -> str:
    d = unpack_move(v)
    m = chess.Move(d["from_sq"], d["to_sq"], promotion=PROMO_INV.get(d["promo"]))
    return m.uci()


def packed_to_move(v: int) -> chess.Move:
    d = unpack_move(v)
    return chess.Move(d["from_sq"], d["to_sq"], promotion=PROMO_INV.get(d["promo"]))


# ---------------------------------------------------------------------------
# Canonicalisation
# ---------------------------------------------------------------------------

def canonical_board(board: chess.Board) -> tuple[chess.Board, bool]:
    """Return (board with White to move, flipped?).

    Uses python-chess `mirror()` which flips vertically and swaps colours,
    correctly transforming castling rights and the en-passant square.
    """
    if board.turn == chess.WHITE:
        return board, False
    return board.mirror(), True


def flip_square(sq: int) -> int:
    return sq ^ 56


def flip_move(move: chess.Move) -> chess.Move:
    return chess.Move(flip_square(move.from_square), flip_square(move.to_square),
                      promotion=move.promotion)


# ---------------------------------------------------------------------------
# Board -> feature arrays
# ---------------------------------------------------------------------------
# Per-square categorical: 0 = empty, 1..6 = own P,N,B,R,Q,K, 7..12 = opp
N_PIECE_TOKENS = 13
# Per-square binary extras
SQ_EXTRA = ["last_from", "last_to", "ep_square", "own_backrank_castle"]
N_SQ_EXTRA = len(SQ_EXTRA)

GLOBAL_FEATS = [
    "own_oo", "own_ooo", "opp_oo", "opp_ooo",
    "has_ep",
    "halfmove_clock_n", "fullmove_n", "repetition_n",
    "own_pawns_n", "own_knights_n", "own_bishops_n", "own_rooks_n", "own_queens_n",
    "opp_pawns_n", "opp_knights_n", "opp_bishops_n", "opp_rooks_n", "opp_queens_n",
    "in_check", "material_diff_n",
]
N_GLOBAL = len(GLOBAL_FEATS)

_PT_ORDER = [chess.PAWN, chess.KNIGHT, chess.BISHOP, chess.ROOK, chess.QUEEN, chess.KING]
_PIECE_VAL = {chess.PAWN: 1, chess.KNIGHT: 3, chess.BISHOP: 3, chess.ROOK: 5,
              chess.QUEEN: 9, chess.KING: 0}


def encode_board(cboard: chess.Board, last_move: chess.Move | None = None,
                 repetition: int = 0):
    """Encode a *canonical* (White-to-move) board.

    Returns (squares int8[64], extras int8[64,N_SQ_EXTRA], glob float32[N_GLOBAL]).
    """
    sq = np.zeros(64, dtype=np.int8)
    for s, piece in cboard.piece_map().items():
        idx = _PT_ORDER.index(piece.piece_type) + 1
        if piece.color == chess.BLACK:
            idx += 6
        sq[s] = idx

    extras = np.zeros((64, N_SQ_EXTRA), dtype=np.int8)
    if last_move is not None:
        extras[last_move.from_square, 0] = 1
        extras[last_move.to_square, 1] = 1
    if cboard.ep_square is not None:
        extras[cboard.ep_square, 2] = 1
    if cboard.has_kingside_castling_rights(chess.WHITE):
        extras[chess.H1, 3] = 1
        extras[chess.E1, 3] = 1
    if cboard.has_queenside_castling_rights(chess.WHITE):
        extras[chess.A1, 3] = 1
        extras[chess.E1, 3] = 1

    g = np.zeros(N_GLOBAL, dtype=np.float32)
    g[0] = cboard.has_kingside_castling_rights(chess.WHITE)
    g[1] = cboard.has_queenside_castling_rights(chess.WHITE)
    g[2] = cboard.has_kingside_castling_rights(chess.BLACK)
    g[3] = cboard.has_queenside_castling_rights(chess.BLACK)
    g[4] = cboard.ep_square is not None
    g[5] = min(cboard.halfmove_clock, 100) / 100.0
    g[6] = min(cboard.fullmove_number, 120) / 120.0
    g[7] = min(repetition, 3) / 3.0
    mat = 0
    for i, pt in enumerate(_PT_ORDER[:5]):
        nw = len(cboard.pieces(pt, chess.WHITE))
        nb = len(cboard.pieces(pt, chess.BLACK))
        g[8 + i] = nw / 8.0
        g[13 + i] = nb / 8.0
        mat += _PIECE_VAL[pt] * (nw - nb)
    g[18] = cboard.is_check()
    g[19] = np.tanh(mat / 10.0)
    return sq, extras, g


def encode_position(board: chess.Board, last_move: chess.Move | None = None,
                    repetition: int = 0):
    """Canonicalise then encode. Returns (squares, extras, glob, flipped)."""
    cb, flipped = canonical_board(board)
    lm = last_move
    if flipped and lm is not None:
        lm = flip_move(lm)
    sq, ex, g = encode_board(cb, lm, repetition)
    return sq, ex, g, flipped


def legal_packed(board: chess.Board):
    """Return (packed candidate array int32[L], canonical board, flipped)."""
    cb, flipped = canonical_board(board)
    return np.array([pack_move(cb, m) for m in cb.legal_moves], dtype=np.int32), cb, flipped