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@ -33,8 +33,8 @@ def main(): |
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shield_value = args.shield_value |
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shield_comparison = args.shield_comparison |
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log_dir = create_log_dir(args) |
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new_logger = Logger(log_dir, output_formats=[CSVOutputFormat(os.path.join(log_dir, f"progress_{expname(args)}.csv")), TensorBoardOutputFormat(log_dir)]) |
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#new_logger = Logger(log_dir, output_formats=[CSVOutputFormat(os.path.join(log_dir, f"progress_{expname(args)}.csv")), TensorBoardOutputFormat(log_dir), HumanOutputFormat(sys.stdout)]) |
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#new_logger = Logger(log_dir, output_formats=[CSVOutputFormat(os.path.join(log_dir, f"progress_{expname(args)}.csv")), TensorBoardOutputFormat(log_dir)]) |
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new_logger = Logger(log_dir, output_formats=[CSVOutputFormat(os.path.join(log_dir, f"progress_{expname(args)}.csv")), TensorBoardOutputFormat(log_dir), HumanOutputFormat(sys.stdout)]) |
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if shield_needed(args.shielding): |
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@ -89,7 +89,7 @@ def main(): |
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imageAndVideoCallback = ImageRecorderCallback(eval_env, render_freq, n_eval_episodes=1, evaluation_method=evaluate_policy, log_dir=log_dir, deterministic=True, verbose=0) |
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model.learn(steps,callback=[imageAndVideoCallback, InfoCallback(), evalCallback]) |
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model.learn(steps,callback=[imageAndVideoCallback, InfoCallback()]) |
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#vec_env = model.get_env() |
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#obs = vec_env.reset() |
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