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| import pytest | |
| from easydict import EasyDict | |
| from ding.config import compile_config_parallel | |
| from ding.worker.coordinator.one_vs_one_parallel_commander import OneVsOneCommander | |
| def setup_1v1commander(): | |
| nstep = 1 | |
| eval_interval = 5 | |
| main_config = dict( | |
| exp_name='one_vs_one_test', | |
| env=dict( | |
| collector_env_num=8, | |
| collector_episode_num=2, | |
| evaluator_env_num=5, | |
| evaluator_episode_num=1, | |
| stop_value=20, | |
| ), | |
| policy=dict( | |
| cuda=False, | |
| model=dict( | |
| obs_shape=[4, 84, 84], | |
| action_shape=3, | |
| encoder_kwargs=dict(encoder_type='conv2d'), | |
| ), | |
| nstep=nstep, | |
| learn=dict( | |
| batch_size=32, | |
| learning_rate=0.0001, | |
| weight_decay=0., | |
| algo=dict( | |
| target_update_freq=500, | |
| discount_factor=0.99, | |
| nstep=nstep, | |
| ), | |
| learner=dict( | |
| learner_num=1, | |
| send_policy_freq=1, | |
| ), | |
| ), | |
| collect=dict( | |
| traj_len=15, | |
| algo=dict(nstep=nstep), | |
| collector=dict( | |
| collector_num=2, | |
| update_policy_second=3, | |
| ), | |
| ), | |
| other=dict( | |
| eps=dict( | |
| type='linear', | |
| start=1., | |
| end=0.005, | |
| decay=1000000, | |
| ), | |
| commander=dict( | |
| collector_task_space=2, | |
| learner_task_space=1, | |
| eval_interval=eval_interval, | |
| league=dict(naive_sp_player=dict(one_phase_step=1000, ), ), | |
| ), | |
| replay_buffer=dict(), | |
| ), | |
| ), | |
| ) | |
| main_config = EasyDict(main_config) | |
| create_config = dict( | |
| env=dict( | |
| # 1v1 commander should use “competitive_rl”. | |
| # However, because this env is hard to install, we use "cartpole" instead. | |
| # But commander does not need a real env, it is just preserved to use `compile_config_parallel`. | |
| type='cartpole', | |
| import_names=['dizoo.classic_control.cartpole.envs.cartpole_env'], | |
| ), | |
| env_manager=dict(type='base'), | |
| policy=dict(type='dqn_command'), | |
| learner=dict(type='base', import_names=['ding.worker.learner.base_learner']), | |
| collector=dict( | |
| type='zergling', | |
| import_names=['ding.worker.collector.zergling_parallel_collector'], | |
| ), | |
| commander=dict( | |
| type='one_vs_one', | |
| import_names=['ding.worker.coordinator.one_vs_one_parallel_commander'], | |
| ), | |
| comm_learner=dict( | |
| type='flask_fs', | |
| import_names=['ding.worker.learner.comm.flask_fs_learner'], | |
| ), | |
| comm_collector=dict( | |
| type='flask_fs', | |
| import_names=['ding.worker.collector.comm.flask_fs_collector'], | |
| ), | |
| league=dict(type='one_vs_one'), | |
| ) | |
| system_config = dict( | |
| coordinator=dict(), | |
| path_data='./data', | |
| path_policy='./policy', | |
| communication_mode='auto', | |
| learner_gpu_num=1, | |
| ) | |
| system_config = EasyDict(system_config) | |
| create_config = EasyDict(create_config) | |
| config = compile_config_parallel(main_config, create_cfg=create_config, system_cfg=system_config) | |
| return OneVsOneCommander(config['main']) | |