67 lines
1.3 KiB
Python
67 lines
1.3 KiB
Python
from network import Network
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import tensorflow as tf
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import random
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import numpy as np
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from board import Board
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import main
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config = main.config.copy()
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config['model'] = "player_testings"
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config['ply'] = "1"
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config['board_representation'] = 'quack-fat'
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network = Network(config, config['model'])
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network.restore_model()
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initial_state = Board.initial_state
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initial_state_1 = ( 0,
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0, 0, 0, 2, 0, -5,
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0, -3, 0, 0, 0, 0,
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-5, 0, 0, 0, 3, 5,
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0, 0, 0, 0, 5, -2,
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0 )
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initial_state_2 = ( 0,
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-5, -5, -3, -2, 0, 0,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 15, 0, 0,
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0, 0, 0, 0, 0, 0,
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0 )
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boards = {initial_state,
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initial_state_1,
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initial_state_2 }
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# board = network.board_trans_func(Board.initial_state, 1)
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# pair = network.make_move(Board.initial_state, [3,2], 1)
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# print(pair[1])
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# network.do_backprop(board, 0.9)
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# network.print_variables()
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# network.save_model(2)
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# print(network.calculate_1_ply(Board.initial_state, [3,2], 1))
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diff = [0, 0]
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val = network.eval_state(Board.board_features_quack_fat(initial_state, 1))
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print(val)
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diff[0] += abs(-1-val)
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diff[1] += 1
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print(diff[1]) |