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62 lines
3.0 KiB
Python
62 lines
3.0 KiB
Python
import copy
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from rl_coach.base_parameters import VisualizationParameters
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from rl_coach.environments.carla_environment import CarlaEnvironmentParameters, CameraTypes, CarlaInputFilter
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from rl_coach.environments.environment import MaxDumpMethod, SelectedPhaseOnlyDumpMethod
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from rl_coach.graph_managers.basic_rl_graph_manager import BasicRLGraphManager
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from rl_coach.graph_managers.graph_manager import ScheduleParameters
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from rl_coach.agents.ddpg_agent import DDPGAgentParameters
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from rl_coach.core_types import TrainingSteps, EnvironmentEpisodes, EnvironmentSteps, RunPhase
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####################
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# Graph Scheduling #
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####################
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schedule_params = ScheduleParameters()
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schedule_params.improve_steps = TrainingSteps(10000000000)
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schedule_params.steps_between_evaluation_periods = EnvironmentEpisodes(20)
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schedule_params.evaluation_steps = EnvironmentEpisodes(1)
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schedule_params.heatup_steps = EnvironmentSteps(1000)
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#########
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# Agent #
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#########
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agent_params = DDPGAgentParameters()
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agent_params.algorithm.num_consecutive_playing_steps = EnvironmentSteps(4)
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# front camera
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agent_params.network_wrappers['actor'].input_embedders_parameters['forward_camera'] = \
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agent_params.network_wrappers['actor'].input_embedders_parameters.pop('observation')
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agent_params.network_wrappers['critic'].input_embedders_parameters['forward_camera'] = \
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agent_params.network_wrappers['critic'].input_embedders_parameters.pop('observation')
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# left camera
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agent_params.network_wrappers['actor'].input_embedders_parameters['left_camera'] = \
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copy.deepcopy(agent_params.network_wrappers['actor'].input_embedders_parameters['forward_camera'])
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agent_params.network_wrappers['critic'].input_embedders_parameters['left_camera'] = \
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copy.deepcopy(agent_params.network_wrappers['critic'].input_embedders_parameters['forward_camera'])
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# right camera
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agent_params.network_wrappers['actor'].input_embedders_parameters['right_camera'] = \
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copy.deepcopy(agent_params.network_wrappers['actor'].input_embedders_parameters['forward_camera'])
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agent_params.network_wrappers['critic'].input_embedders_parameters['right_camera'] = \
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copy.deepcopy(agent_params.network_wrappers['critic'].input_embedders_parameters['forward_camera'])
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agent_params.input_filter = CarlaInputFilter()
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agent_params.input_filter.copy_filters_from_one_observation_to_another('forward_camera', 'left_camera')
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agent_params.input_filter.copy_filters_from_one_observation_to_another('forward_camera', 'right_camera')
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###############
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# Environment #
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###############
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env_params = CarlaEnvironmentParameters()
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env_params.level = 'town1'
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env_params.cameras = [CameraTypes.FRONT, CameraTypes.LEFT, CameraTypes.RIGHT]
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vis_params = VisualizationParameters()
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vis_params.video_dump_methods = [SelectedPhaseOnlyDumpMethod(RunPhase.TEST), MaxDumpMethod()]
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vis_params.dump_mp4 = False
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graph_manager = BasicRLGraphManager(agent_params=agent_params, env_params=env_params,
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schedule_params=schedule_params, vis_params=vis_params)
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