MemoryError. When train DistributedRL after an hour.

[JazzTao]

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Problem description

When I train DistributedRL:
https://github.com/Microsoft/AutonomousDrivingCookbook/blob/master/DistributedRL/LaunchLocalTrainingJob.ipynb
it works at first. After about one hour,I get the error below.
(PS: Actually I changed “threshold=np.nan” to "threshold=sys.maxsize" which in the "distributed_agent.py" Line 609 to let it work at the first time I run “train.bat”. I don't know if it matters.)

My english is not very good. I don't know if I express it clearly.

Problem details

Start time: 2019-04-15 07:23:33.036246, end time: 2019-04-15 07:23:45.755073
Percent random actions: 0.10204081632653061
Num total actions: 98
Generating 98 minibatches...
Sampling Experiences.
Publishing AirSim Epoch.
Publishing epoch data and getting latest model from parameter server...
Traceback (most recent call last):
File "distributed_agent.py", line 643, in
agent.start()
File "distributed_agent.py", line 80, in start
self.__run_function()
File "distributed_agent.py", line 175, in __run_function
self.__publish_batch_and_update_model(sampled_experiences, frame_count)
File "distributed_agent.py", line 401, in __publish_batch_and_update_model
gradients = self.__model.get_gradient_update_from_batches(batches)
File "E:\File\Train_Airsim\AD_Cookbook_AirSim\python36_DRL\Share\scripts_downpour\app\rl_model.py", line 135, in get_gradient_update_from_batches
post_states = np.array(batches['post_states'])
MemoryError

Experiment/Environment details

• Tutorial used: DistributedRL
• Environment used: neighborhood
• Versions of artifacts used (if applicable): tensorflow 1.13.1 ;Python 3.6.2,;Keras 2.1.2;numpy 1.16.2
  *The state of my harddisk：C：9.48GB available，E : 25.4GB （DistributedRL‘sworkspace） available
  *My computer equipment：GPU-GTX960M-4G ，Memory-8G，CPU i5-6300HQ

[Zhenlin-Xu]

What is your solution? I came up with the same issue on the newest version. Instead of changing “threshold=np.nan” to "threshold=sys.maxsize", i changed it to "threshold=np.inf" in order to run the script without error coming.

Thank U!