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Avoid Memory Leak in Rollout worker

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ISSUE: When we restore checkpoints, we create new nodes in the
Tensorflow graph. This happens when we assign new value (op node) to
RefVariable in GlobalVariableSaver. With every restore the size of TF
graph increases as new nodes are created and old unused nodes are not
removed from the graph. This causes the memory leak in
restore_checkpoint codepath.

FIX: We reset the Tensorflow graph and recreate the Global, Online and
Target networks on every restore. This ensures that the old unused nodes
in TF graph is dropped.
This commit is contained in:
Gourav Roy
2018-12-25 20:50:34 -08:00
parent 02f2db1264
commit c694766fad
3 changed files with 17 additions and 11 deletions
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4
rl_coach/tests/graph_managers/test_basic_rl_graph_manager.py
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@@ -56,10 +56,6 @@ def test_basic_rl_graph_manager_with_cartpole_dqn_and_repeated_checkpoint_restor
# graph_manager.save_checkpoint()
#
# graph_manager.task_parameters.checkpoint_restore_dir = "./experiments/test/checkpoint"
# graph_manager.agent_params.memory.register_var('memory_backend_params',
# MemoryBackendParameters(store_type=None,
# orchestrator_type=None,
# run_type=str(RunType.ROLLOUT_WORKER)))
# while True:
# graph_manager.restore_checkpoint()
# gc.collect()