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introduce graph_manager.phase_context; make sure that calls to graph_manager.train automatically set training phase

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Zach Dwiel
2018-10-02 16:19:49 -04:00
committed by zach dwiel
parent 7382a142bb
commit 517aac163a
3 changed files with 94 additions and 46 deletions
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37
rl_coach/rollout_worker.py
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@@ -89,36 +89,33 @@ def rollout_worker(graph_manager, checkpoint_dir, data_store, num_workers, polic
task_parameters.__dict__['checkpoint_restore_dir'] = checkpoint_dir
time.sleep(30)
graph_manager.create_graph(task_parameters)
graph_manager.phase = RunPhase.TRAIN
with graph_manager.phase_context(RunPhase.TRAIN):
error_compensation = 100
error_compensation = 100
last_checkpoint = 0
last_checkpoint = 0
act_steps = math.ceil((graph_manager.agent_params.algorithm.num_consecutive_playing_steps.num_steps + error_compensation)/num_workers)
act_steps = math.ceil((graph_manager.agent_params.algorithm.num_consecutive_playing_steps.num_steps + error_compensation)/num_workers)
for i in range(int(graph_manager.improve_steps.num_steps/act_steps)):
for i in range(int(graph_manager.improve_steps.num_steps/act_steps)):
graph_manager.act(EnvironmentSteps(num_steps=act_steps))
graph_manager.act(EnvironmentSteps(num_steps=act_steps))
new_checkpoint = get_latest_checkpoint(checkpoint_dir)
new_checkpoint = get_latest_checkpoint(checkpoint_dir)
if policy_type == 'ON':
while new_checkpoint < last_checkpoint + 1:
if data_store:
data_store.load_from_store()
new_checkpoint = get_latest_checkpoint(checkpoint_dir)
if policy_type == 'ON':
while new_checkpoint < last_checkpoint + 1:
if data_store:
data_store.load_from_store()
new_checkpoint = get_latest_checkpoint(checkpoint_dir)
graph_manager.restore_checkpoint()
if policy_type == "OFF":
if new_checkpoint > last_checkpoint:
graph_manager.restore_checkpoint()
last_checkpoint = new_checkpoint
if policy_type == "OFF":
graph_manager.phase = RunPhase.UNDEFINED
if new_checkpoint > last_checkpoint:
graph_manager.restore_checkpoint()
last_checkpoint = new_checkpoint
def main():