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67 lines
2.7 KiB
Python
67 lines
2.7 KiB
Python
from rl_coach.base_parameters import VisualizationParameters, PresetValidationParameters
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from rl_coach.environments.gym_environment import Mujoco
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from rl_coach.filters.filter import NoInputFilter, NoOutputFilter
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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.memories.memory import MemoryGranularity
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from rl_coach.schedules import ConstantSchedule
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from rl_coach.agents.bootstrapped_dqn_agent import BootstrappedDQNAgentParameters
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from rl_coach.core_types import EnvironmentEpisodes, EnvironmentSteps
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N = 20
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num_output_head_copies = 20
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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 = EnvironmentEpisodes(2000)
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schedule_params.steps_between_evaluation_periods = EnvironmentEpisodes(10)
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schedule_params.evaluation_steps = EnvironmentEpisodes(1)
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schedule_params.heatup_steps = EnvironmentSteps(N)
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####################
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# DQN Agent Params #
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####################
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agent_params = BootstrappedDQNAgentParameters()
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agent_params.network_wrappers['main'].learning_rate = 0.00025
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agent_params.memory.max_size = (MemoryGranularity.Transitions, 1000000)
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agent_params.algorithm.discount = 0.99
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agent_params.algorithm.num_consecutive_playing_steps = EnvironmentSteps(4)
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agent_params.network_wrappers['main'].num_output_head_copies = num_output_head_copies
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agent_params.network_wrappers['main'].rescale_gradient_from_head_by_factor = [1.0/num_output_head_copies]*num_output_head_copies
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agent_params.exploration.bootstrapped_data_sharing_probability = 1.0
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agent_params.exploration.architecture_num_q_heads = num_output_head_copies
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agent_params.exploration.epsilon_schedule = ConstantSchedule(0)
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agent_params.input_filter = NoInputFilter()
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agent_params.output_filter = NoOutputFilter()
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###############
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# Environment #
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###############
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env_params = Mujoco()
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env_params.level = 'rl_coach.environments.toy_problems.exploration_chain:ExplorationChain'
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env_params.additional_simulator_parameters = {'chain_length': N, 'max_steps': N+7}
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vis_params = VisualizationParameters()
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########
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# Test #
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########
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# currently no test here as bootstrapped_dqn seems to be broken
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# preset_validation_params = PresetValidationParameters()
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# preset_validation_params.test = True
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# preset_validation_params.min_reward_threshold = 1600
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# preset_validation_params.max_episodes_to_achieve_reward = 70
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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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# preset_validation_params=preset_validation_params)
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