File size: 2,748 Bytes
cf2aacd | 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 | import numpy as np
# Bitboard Constants
BOARD_SIZE = 8
FULL_MASK = 0xFFFFFFFFFFFFFFFF
def popcount(x):
"""Counts set bits in a 64-bit integer."""
return bin(x).count('1')
def bit_to_row_col(bit_mask):
"""Converts a single bit mask to (row, col) coordinates."""
if bit_mask == 0:
return -1, -1
# Find the index of the set bit (0-63)
# Assumes only one bit is set
idx = bit_mask.bit_length() - 1
# Edax/Othello usually maps MSB to A1 (0,0) or LSB to H8 (7,7)
# Let's align with Edax: A1 is usually high bit.
# Standard: index 63 is A1, index 0 is H8.
# row = (63 - idx) // 8
# col = (63 - idx) % 8
# However, standard bit manipulation often uses LSB=0.
# Let's check Edax conventions later, but for now standard math:
row = (63 - idx) // 8
col = (63 - idx) % 8
return row, col
def get_bit(row, col):
"""Returns a bitmask with a single bit set at (row, col)."""
shift = 63 - (row * 8 + col)
return 1 << shift
def make_input_planes(player_bb, opponent_bb):
"""
Converts bitboards into a 3x8x8 input tensor for the Neural Network.
Plane 0: Player pieces (1 if present, 0 otherwise)
Plane 1: Opponent pieces (1 if present, 0 otherwise)
Plane 2: Constant 1 (indicating it's the player's turn, or generally providing board usage context)
Some implementations use 'Valid Moves' here instead.
Let's use a constant plane for now as per AlphaZero standard,
or we can update to valid moves if we have them handy.
"""
planes = np.zeros((3, 8, 8), dtype=np.float32)
# Fill Plane 0 (Player)
for r in range(8):
for c in range(8):
mask = get_bit(r, c)
if player_bb & mask:
planes[0, r, c] = 1.0
# Fill Plane 1 (Opponent)
for r in range(8):
for c in range(8):
mask = get_bit(r, c)
if opponent_bb & mask:
planes[1, r, c] = 1.0
# Fill Plane 2 (Constant / Color)
# Often for single-network (canonical form), this might just be 1s.
planes[2, :, :] = 1.0
import torch
return torch.tensor(planes).unsqueeze(0) # Add batch dimension: (1, 3, 8, 8)
def print_board(black_bb, white_bb):
"""Prints the board state using B/W symbols."""
print(" A B C D E F G H")
for r in range(8):
line = f"{r+1} "
for c in range(8):
mask = get_bit(r, c)
if black_bb & mask:
line += "B "
elif white_bb & mask:
line += "W "
else:
line += ". "
print(line)
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