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45 lines
1.8 KiB
Python
45 lines
1.8 KiB
Python
from rl_coach.agents.bc_agent import BCAgentParameters
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from rl_coach.base_parameters import VisualizationParameters, PresetValidationParameters
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from rl_coach.core_types import TrainingSteps, EnvironmentEpisodes, EnvironmentSteps
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from rl_coach.environments.gym_environment import Atari
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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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####################
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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 = TrainingSteps(500)
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schedule_params.evaluation_steps = EnvironmentEpisodes(5)
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schedule_params.heatup_steps = EnvironmentSteps(0)
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#########
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# Agent #
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#########
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agent_params = BCAgentParameters()
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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.memory.discount = 0.99
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agent_params.algorithm.discount = 0.99
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agent_params.algorithm.num_consecutive_playing_steps = EnvironmentSteps(0)
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agent_params.memory.load_memory_from_file_path = 'datasets/montezuma_revenge.p'
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###############
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# Environment #
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###############
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env_params = Atari(level='MontezumaRevenge-v0')
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env_params.random_initialization_steps = 30
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########
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# Test #
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########
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preset_validation_params = PresetValidationParameters()
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preset_validation_params.test_using_a_trace_test = 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=VisualizationParameters(),
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preset_validation_params=preset_validation_params)
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