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network_imporvements branch merge

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This commit is contained in:
Shadi Endrawis
2018-10-02 13:41:46 +03:00
parent 72ea933384
commit 51726a5b80
110 changed files with 1639 additions and 1161 deletions
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rl_coach/presets/BitFlip_DQN_HER.py
+6 -9
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@@ -1,10 +1,10 @@
from rl_coach.agents.dqn_agent import DQNAgentParameters
from rl_coach.architectures.tensorflow_components.architecture import Dense
from rl_coach.architectures.tensorflow_components.embedders.embedder import InputEmbedderParameters
from rl_coach.architectures.tensorflow_components.layers import Dense
from rl_coach.base_parameters import VisualizationParameters, EmbedderScheme, \
PresetValidationParameters
from rl_coach.core_types import TrainingSteps, EnvironmentEpisodes, EnvironmentSteps
from rl_coach.architectures.tensorflow_components.embedders.embedder import InputEmbedderParameters
from rl_coach.environments.gym_environment import Mujoco
from rl_coach.environments.gym_environment import GymVectorEnvironment
from rl_coach.graph_managers.basic_rl_graph_manager import BasicRLGraphManager
from rl_coach.graph_managers.graph_manager import ScheduleParameters
from rl_coach.memories.episodic.episodic_hindsight_experience_replay import \
@@ -30,7 +30,7 @@ schedule_params.heatup_steps = EnvironmentSteps(0)
agent_params = DQNAgentParameters()
agent_params.network_wrappers['main'].learning_rate = 0.001
agent_params.network_wrappers['main'].batch_size = 128
agent_params.network_wrappers['main'].middleware_parameters.scheme = [Dense([256])]
agent_params.network_wrappers['main'].middleware_parameters.scheme = [Dense(256)]
agent_params.network_wrappers['main'].input_embedders_parameters = {
'state': InputEmbedderParameters(scheme=EmbedderScheme.Empty),
'desired_goal': InputEmbedderParameters(scheme=EmbedderScheme.Empty)}
@@ -55,13 +55,10 @@ agent_params.memory.goals_space = GoalsSpace(goal_name='state',
###############
# Environment #
###############
env_params = Mujoco()
env_params.level = 'rl_coach.environments.toy_problems.bit_flip:BitFlip'
env_params = GymVectorEnvironment(level='rl_coach.environments.toy_problems.bit_flip:BitFlip')
env_params.additional_simulator_parameters = {'bit_length': bit_length, 'mean_zero': True}
env_params.custom_reward_threshold = -bit_length + 1
vis_params = VisualizationParameters()
# currently no tests for this preset as the max reward can be accidently achieved. will be fixed with trace based tests.
########
@@ -73,7 +70,7 @@ preset_validation_params.min_reward_threshold = -15
preset_validation_params.max_episodes_to_achieve_reward = 10000
graph_manager = BasicRLGraphManager(agent_params=agent_params, env_params=env_params,
schedule_params=schedule_params, vis_params=vis_params,
schedule_params=schedule_params, vis_params=VisualizationParameters(),
preset_validation_params=preset_validation_params)