Added board-rep as cli argument, to state which input-board-rep to use.
Also fixed weird nesting of difference_in_values.
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parent
1f8485f54e
commit
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6
main.py
6
main.py
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@ -33,6 +33,9 @@ parser.add_argument('--list-models', action='store_true',
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help='list all known models')
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help='list all known models')
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parser.add_argument('--force-creation', action='store_true',
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parser.add_argument('--force-creation', action='store_true',
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help='force model creation if model does not exist')
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help='force model creation if model does not exist')
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parser.add_argument('--board-rep', action='store', dest='board_rep',
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default='tesauro',
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help='name of board representation to use as input to neural network')
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parser.add_argument('--use-baseline', action='store_true',
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parser.add_argument('--use-baseline', action='store_true',
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help='use the baseline model, note, has size 28')
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help='use the baseline model, note, has size 28')
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@ -55,7 +58,7 @@ config = {
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'train_perpetually': args.train_perpetually,
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'train_perpetually': args.train_perpetually,
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'model_storage_path': 'models',
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'model_storage_path': 'models',
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'bench_storage_path': 'bench',
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'bench_storage_path': 'bench',
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'board_representation': 'quack-fat',
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'board_representation': args.board_rep,
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'force_creation': args.force_creation,
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'force_creation': args.force_creation,
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'use_baseline': args.use_baseline
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'use_baseline': args.use_baseline
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}
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}
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@ -83,6 +86,7 @@ def log_train_outcome(outcome, diff_in_values, trained_eps = 0, log_path = os.pa
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'time': int(time.time()),
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'time': int(time.time()),
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'average_diff_in_vals': diff_in_values/len(outcome)
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'average_diff_in_vals': diff_in_values/len(outcome)
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}
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}
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with open(log_path, 'a+') as f:
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with open(log_path, 'a+') as f:
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f.write("{time};{trained_eps};{count};{sum};{mean};{average_diff_in_vals}".format(**format_vars) + "\n")
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f.write("{time};{trained_eps};{count};{sum};{mean};{average_diff_in_vals}".format(**format_vars) + "\n")
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@ -582,6 +582,6 @@ class Network:
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writer.close()
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writer.close()
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return outcomes, difference_in_vals
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return outcomes, difference_in_vals[0][0]
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