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improve ddpg

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This commit is contained in:
yangdsh
2019-11-09 01:58:10 +00:00
committed by Dana Van Aken
parent 67a4a70c09
commit 21fce27291
5 changed files with 79 additions and 59 deletions
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11
server/website/website/settings/constants.py
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@@ -77,7 +77,16 @@ DNN_DEBUG_INTERVAL = 100
DDPG_BATCH_SIZE = 32
# Learning rate of actor network
ACTOR_LEARNING_RATE = 0.01
ACTOR_LEARNING_RATE = 0.02
# Learning rate of critic network
CRITIC_LEARNING_RATE = 0.001
# Number of update epochs per iteration
UPDATE_EPOCHS = 30
# The number of hidden units in each layer of the actor MLP
ACTOR_HIDDEN_SIZES = [128, 128, 64]
# The number of hidden units in each layer of the critic MLP
CRITIC_HIDDEN_SIZES = [64, 128, 64]

16
server/website/website/tasks/async_tasks.py
View File

@@ -31,7 +31,8 @@ from website.settings import (DEFAULT_LENGTH_SCALE, DEFAULT_MAGNITUDE,
DEFAULT_EPSILON, MAX_ITER, GPR_EPS,
DEFAULT_SIGMA_MULTIPLIER, DEFAULT_MU_MULTIPLIER,
DDPG_BATCH_SIZE, ACTOR_LEARNING_RATE,
CRITIC_LEARNING_RATE,
CRITIC_LEARNING_RATE, UPDATE_EPOCHS,
ACTOR_HIDDEN_SIZES, CRITIC_HIDDEN_SIZES,
DNN_TRAIN_ITER, DNN_EXPLORE, DNN_EXPLORE_ITER,
DNN_NOISE_SCALE_BEGIN, DNN_NOISE_SCALE_END,
DNN_DEBUG, DNN_DEBUG_INTERVAL)
@@ -278,12 +279,9 @@ def train_ddpg(result_id):
result = Result.objects.get(pk=result_id)
session = Result.objects.get(pk=result_id).session
session_results = Result.objects.filter(session=session,
creation_time__lt=result.creation_time)
creation_time__lte=result.creation_time)
result_info = {}
result_info['newest_result_id'] = result_id
if len(session_results) == 0:
LOG.info('No previous result. Abort.')
return result_info
# Extract data from result
result = Result.objects.filter(pk=result_id)
@@ -332,13 +330,14 @@ def train_ddpg(result_id):
# Update ddpg
ddpg = DDPG(n_actions=knob_num, n_states=metric_num, alr=ACTOR_LEARNING_RATE,
clr=CRITIC_LEARNING_RATE, gamma=0, batch_size=DDPG_BATCH_SIZE)
clr=CRITIC_LEARNING_RATE, gamma=0, batch_size=DDPG_BATCH_SIZE,
a_hidden_sizes=ACTOR_HIDDEN_SIZES, c_hidden_sizes=CRITIC_HIDDEN_SIZES)
if session.ddpg_actor_model and session.ddpg_critic_model:
ddpg.set_model(session.ddpg_actor_model, session.ddpg_critic_model)
if session.ddpg_reply_memory:
ddpg.replay_memory.set(session.ddpg_reply_memory)
ddpg.add_sample(normalized_metric_data, knob_data, reward, normalized_metric_data)
for _ in range(25):
for _ in range(UPDATE_EPOCHS):
ddpg.update()
session.ddpg_actor_model, session.ddpg_critic_model = ddpg.get_model()
session.ddpg_reply_memory = ddpg.replay_memory.get()
@@ -362,7 +361,8 @@ def configuration_recommendation_ddpg(result_info): # pylint: disable=invalid-n
knob_num = len(knob_labels)
metric_num = len(metric_data)
ddpg = DDPG(n_actions=knob_num, n_states=metric_num)
ddpg = DDPG(n_actions=knob_num, n_states=metric_num, a_hidden_sizes=ACTOR_HIDDEN_SIZES,
c_hidden_sizes=CRITIC_HIDDEN_SIZES)
if session.ddpg_actor_model is not None and session.ddpg_critic_model is not None:
ddpg.set_model(session.ddpg_actor_model, session.ddpg_critic_model)
if session.ddpg_reply_memory is not None: