From 221e83abd779413c49b9376692f4d5392b950aa3 Mon Sep 17 00:00:00 2001 From: Alexander Munch-Hansen Date: Fri, 15 Jun 2018 01:19:51 +0200 Subject: [PATCH] Sorry stoffer-boi --- app.py | 14 +- board.py | 41 ++ main.py | 4 - models/exp_decay_fat/checkpoint | 2 + models/exp_decay_fat/episodes_trained | 1 + models/exp_decay_fat/logs/eval.log | 615 ++++++++++++++++++ models/exp_decay_fat/logs/train.log | 107 +++ .../model.ckpt-10043695.data-00000-of-00001 | Bin 0 -> 70408 bytes .../exp_decay_fat/model.ckpt-10043695.index | Bin 0 -> 234 bytes models/exp_decay_fat/model.ckpt-10043695.meta | Bin 0 -> 224052 bytes .../model.ckpt-10153974.data-00000-of-00001 | Bin 0 -> 70408 bytes .../exp_decay_fat/model.ckpt-10153974.index | Bin 0 -> 234 bytes models/exp_decay_fat/model.ckpt-10153974.meta | Bin 0 -> 224052 bytes .../model.ckpt-1017420.data-00000-of-00001 | Bin 0 -> 70408 bytes models/exp_decay_fat/model.ckpt-1017420.index | Bin 0 -> 234 bytes models/exp_decay_fat/model.ckpt-1017420.meta | Bin 0 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config['model']) sess = tf.Session() -network.restore_model(sess) sess.run(tf.global_variables_initializer()) - - +network.restore_model(sess) def calc_move_sets(from_board, roll, player): board = from_board @@ -59,8 +57,8 @@ def calc_move_sets(from_board, roll, player): def tmp_name(from_board, to_board, roll, player, total_moves, is_quad=False): sets = calc_move_sets(from_board, roll, player) return_board = from_board - print("To board:\n",to_board) - print("All sets:\n",sets) + # print("To board:\n",to_board) + # print("All sets:\n",sets) for idx, board_set in enumerate(sets): board_set[0] = list(board_set[0]) # print(to_board) @@ -110,8 +108,7 @@ def pubeval_move(): data = request.get_json(force=True) board = [int(x) for x in data['board'].split(',')] player = int(data['player']) - - roll = (random.randrange(1,7), random.randrange(1,7)) + roll = [int(x) for x in data['roll'].split(',')] board, value = Eval.make_pubeval_move(tuple(board), player, roll) print("Doing pubeval move") @@ -124,8 +121,7 @@ def network_move(): data = request.get_json(force=True) board = [int(x) for x in data['board'].split(',')] player = int(data['player']) - - roll = (random.randrange(1,7), random.randrange(1,7)) + roll = [int(x) for x in data['roll'].split(',')] board, value = network.make_move(sess, tuple(board), roll, player) diff --git a/board.py b/board.py index 07ac630..ef1fd06 100644 --- a/board.py +++ b/board.py @@ -101,6 +101,47 @@ class Board: return np.array(board_rep).reshape(1,198) + @staticmethod + def board_features_tesauro_fat(board, cur_player): + def ordinary_trans(val, player): + abs_val = val*player + if abs_val <= 0: + return (0, 0, 0, 0, 0, 0, 0, 0, 0) + elif abs_val == 1: + return (1, 0, 0, 0, 0, 0, 0, 0, 0) + elif abs_val == 2: + return (1, 1, 0, 0, 0, 0, 0, 0, 0) + elif abs_val == 3: + return (1, 1, 1, 0, 0, 0, 0, 0, 0) + elif abs_val == 4: + return (1, 1, 1, 1, 0, 0, 0, 0, 0) + elif abs_val == 5: + return (1, 1, 1, 1, 1, 0, 0, 0, 0) + elif abs_val == 6: + return (1, 1, 1, 1, 1, 1, 0, 0, 0) + elif abs_val == 7: + return (1, 1, 1, 1, 1, 1, 1, 0, 0) + elif abs_val == 8: + return (1, 1, 1, 1, 1, 1, 1, 1, 0) + else: + return (1, 1, 1, 1, 1, 1, 1, 1, (abs_val - 9) / 2) + + + def bar_trans(board, player): + if player == 1: return (abs(board[0]/2),) + elif player == -1: return (abs(board[25]/2),) + + board_rep = [] + for player in [1, -1]: + for x in board[1:25]: + board_rep += ordinary_trans(x, player) + board_rep += bar_trans(board, player) + board_rep += (15 - Board.num_of_checkers_for_player(board, player),) + + board_rep += ([1, 0] if cur_player == 1 else [1,0]) + + return np.array(board_rep).reshape(1, len(board_rep)) + @staticmethod def board_features_tesauro_wrong(board, cur_player): diff --git a/main.py b/main.py index e2e8988..5a94dfa 100644 --- a/main.py +++ b/main.py @@ -36,8 +36,6 @@ parser.add_argument('--force-creation', action='store_true', parser.add_argument('--board-rep', action='store', dest='board_rep', default='tesauro', help='name of board representation to use as input to neural network') -parser.add_argument('--use-baseline', action='store_true', - help='use the baseline model, note, has size 28') args = parser.parse_args() @@ -59,8 +57,6 @@ config = { 'model_storage_path': 'models', 'bench_storage_path': 'bench', 'board_representation': args.board_rep, - 'force_creation': args.force_creation, - 'use_baseline': args.use_baseline } # Create models folder diff --git a/models/exp_decay_fat/checkpoint b/models/exp_decay_fat/checkpoint new file mode 100644 index 0000000..c903b47 --- /dev/null +++ b/models/exp_decay_fat/checkpoint @@ -0,0 +1,2 @@ +model_checkpoint_path: "model.ckpt-11397483" +all_model_checkpoint_paths: "model.ckpt-11397483" diff --git a/models/exp_decay_fat/episodes_trained b/models/exp_decay_fat/episodes_trained new file mode 100644 index 0000000..ab18ea1 --- /dev/null +++ b/models/exp_decay_fat/episodes_trained @@ -0,0 +1 @@ +202615 diff --git a/models/exp_decay_fat/logs/eval.log 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