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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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7
parallel_actor.py
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@@ -128,11 +128,14 @@ if __name__ == "__main__":
def init_fn(scaffold, session):
session.run(init_all_op)
#saver = tf.train.Saver(max_to_keep=None) # uncomment to unlimit number of stored checkpoints
scaffold = tf.train.Scaffold(init_op=init_all_op,
init_fn=init_fn,
ready_op=ready_op,
ready_for_local_init_op=ready_for_local_init_op,
local_init_op=local_init_op)
#saver=saver) # uncomment to unlimit number of stored checkpoints
# Due to awkward tensorflow behavior where the same variable is used to decide whether to restore a model
# (and where from), or just save the model (and where to), we employ the below. In case where a restore folder
@@ -156,6 +159,10 @@ if __name__ == "__main__":
tuning_parameters.sess = sess
for network in agent.networks:
network.set_session(sess)
# if hasattr(network.global_network, 'lock_init'):
# sess.run(network.global_network.lock_init)
# if hasattr(network.global_network, 'release_init'):
# sess.run(network.global_network.release_init)
if tuning_parameters.visualization.tensorboard:
# Write the merged summaries to the current experiment directory