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Parallel agents fixes (#95)

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* Parallel agents related bug fixes: checkpoint restore, tensorboard integration.
Adding narrow networks support.
Reference code for unlimited number of checkpoints
This commit is contained in:
Itai Caspi
2018-05-24 14:24:19 +03:00
committed by GitHub
parent 6c0b59b4de
commit d302168c8c
10 changed files with 75 additions and 41 deletions
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11
presets.py
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@@ -664,8 +664,11 @@ class Humanoid_ClippedPPO(Preset):
def __init__(self):
Preset.__init__(self, ClippedPPO, GymVectorObservation, ExplorationParameters)
self.env.level = 'Humanoid-v1'
self.learning_rate = 0.0001
self.agent.embedder_width = EmbedderWidth.Narrow
self.learning_rate = 0.00001
self.num_heatup_steps = 0
self.evaluation_episodes = 1
self.evaluate_every_x_episodes = 1
self.agent.num_consecutive_training_steps = 1
self.agent.num_consecutive_playing_steps = 2048
self.agent.discount = 0.99
@@ -1337,7 +1340,7 @@ class Breakout_A3C(Preset):
class Carla_A3C(Preset):
def __init__(self):
Preset.__init__(self, ActorCritic, Carla, EntropyExploration)
self.agent.embedder_complexity = EmbedderComplexity.Deep
self.agent.embedder_complexity = EmbedderDepth.Deep
self.agent.policy_gradient_rescaler = 'GAE'
self.learning_rate = 0.0001
self.num_heatup_steps = 0
@@ -1354,7 +1357,7 @@ class Carla_A3C(Preset):
class Carla_DDPG(Preset):
def __init__(self):
Preset.__init__(self, DDPG, Carla, OUExploration)
self.agent.embedder_complexity = EmbedderComplexity.Deep
self.agent.embedder_complexity = EmbedderDepth.Deep
self.learning_rate = 0.0001
self.num_heatup_steps = 1000
self.agent.num_consecutive_training_steps = 5
@@ -1363,7 +1366,7 @@ class Carla_DDPG(Preset):
class Carla_BC(Preset):
def __init__(self):
Preset.__init__(self, BC, Carla, ExplorationParameters)
self.agent.embedder_complexity = EmbedderComplexity.Deep
self.agent.embedder_complexity = EmbedderDepth.Deep
self.agent.load_memory_from_file_path = 'datasets/carla_town1.p'
self.learning_rate = 0.0005
self.num_heatup_steps = 0