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from easydict import EasyDict |
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maze_size = 16 |
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num_actions = 4 |
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maze_pc_config = dict( |
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exp_name="maze_bc_seed0", |
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env=dict( |
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collector_env_num=1, |
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evaluator_env_num=5, |
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n_evaluator_episode=5, |
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env_id='Maze', |
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size=maze_size, |
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wall_type='tunnel', |
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stop_value=1 |
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), |
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policy=dict( |
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cuda=True, |
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maze_size=maze_size, |
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num_actions=num_actions, |
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max_bfs_steps=100, |
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model=dict( |
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obs_shape=[3, maze_size, maze_size], |
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action_shape=num_actions, |
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encoder_hidden_size_list=[ |
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128, |
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256, |
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512, |
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1024, |
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], |
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strides=[1, 1, 1, 1] |
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), |
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learn=dict( |
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batch_size=256, |
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learning_rate=0.005, |
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train_epoch=5000, |
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optimizer='SGD', |
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), |
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eval=dict(evaluator=dict(n_episode=5)), |
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collect=dict(), |
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), |
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) |
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maze_pc_config = EasyDict(maze_pc_config) |
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main_config = maze_pc_config |
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maze_pc_create_config = dict( |
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env=dict( |
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type='maze', |
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import_names=['dizoo.maze.envs.maze_env'], |
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), |
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env_manager=dict(type='subprocess'), |
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policy=dict(type='bc'), |
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) |
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maze_pc_create_config = EasyDict(maze_pc_create_config) |
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create_config = maze_pc_create_config |
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