import chess.uci
import chess.pgn
import sys
import string
import NeuralNet
import os
import ast
# Neural net topology
topology = [64, 44, 18, 1]
# Assigns the existing trained weights in the text file to the neural net.
with open("./TrainedWeightsText.txt", "r") as myfile:
weightsF = myfile.read().replace('\n', '')
weightsL = ast.literal_eval(weightsF)
evalNet = NeuralNet.Net(topology)
for layer in range(len(evalNet.layers) - 1):
for neuron in range(len(evalNet.layers[layer])):
evalNet.layers[layer][neuron].outputWeights = weightsL[layer][neuron]
path = "./PGNFiles/McDonnell.pgn"
# Trains neural network.
with open(path) as f:
count = 0
for n in range(100):
try:
print("GAMECOUNT", n)
game = chess.pgn.read_game(f)
while not game.is_end():
node = game.variations[0]
import copy
from BackEndChess import *
from ChessBoard import *
import random
import NeuralNet
import ast
# Converts string of weights to actual list of weights.
with open("./RealWeights/RealWeights9.txt", "r") as myfile:
weightsF = myfile.read().replace('\n', '')
weightsL = ast.literal_eval(weightsF)
# Sets neural network weights to the weights stored in the text file.
myNet = NeuralNet.Net([64, 44, 18, 1])
for layer in range(len(myNet.layers)-1):
for neuron in range(len(myNet.layers[layer])):
myNet.layers[layer][neuron].outputWeights = weightsL[layer][neuron]
# Translates the chess board that is in the game to a form which is readable by the neural network.
def translateBoard(board):
tBoard = []
for row in range(7, -1, -1):
for col in range(8):
if board[row][col] != None:
if isinstance(board[row][col], Pawn):
if board[row][col].color == "White":
tBoard.append(.01)
else:
tBoard.append(-.01)
