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36 lines
1.5 KiB
Python
36 lines
1.5 KiB
Python
import math
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from rl_coach.agents.ddqn_agent import DDQNAgentParameters
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from rl_coach.architectures.head_parameters import DuelingQHeadParameters
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from rl_coach.base_parameters import VisualizationParameters, MiddlewareScheme, PresetValidationParameters
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from rl_coach.environments.environment import SingleLevelSelection
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from rl_coach.environments.gym_environment import Atari, atari_deterministic_v4, atari_schedule
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from rl_coach.graph_managers.basic_rl_graph_manager import BasicRLGraphManager
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#########
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# Agent #
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#########
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agent_params = DDQNAgentParameters()
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# since we are using Adam instead of RMSProp, we adjust the learning rate as well
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agent_params.network_wrappers['main'].learning_rate = 0.0001
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agent_params.network_wrappers['main'].middleware_parameters.scheme = MiddlewareScheme.Empty
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agent_params.network_wrappers['main'].heads_parameters = \
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[DuelingQHeadParameters(rescale_gradient_from_head_by_factor=1/math.sqrt(2))]
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agent_params.network_wrappers['main'].clip_gradients = 10
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###############
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# Environment #
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###############
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env_params = Atari(level=SingleLevelSelection(atari_deterministic_v4))
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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.trace_test_levels = ['breakout', 'pong', 'space_invaders']
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graph_manager = BasicRLGraphManager(agent_params=agent_params, env_params=env_params,
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schedule_params=atari_schedule, vis_params=VisualizationParameters(),
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preset_validation_params=preset_validation_params)
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