Reinforcement Learning Memory Error
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When I turn on the SaveExperienceBufferWithAgent, I get the following error:
Warning: Unable to save the agent to the directory "savedAgents". Increase the
disk space or check SaveAgentCriteriaValue in training options.
> In rl.train/TrainingManager/saveAgentToDisk (line 653)
In rl.train/TrainingManager/updateDisplaysFromTrainingInfo (line 717)
In rl.train/TrainingManager/update (line 147)
In rl.train.TrainingManager>@(info)update(this,info) (line 437)
In rl.train/Trainer/notifyEpisodeFinishedAndCheckStopTrain (line 56)
In rl.train.SeriesTrainer>iUpdateEpisodeFinished (line 31)
In rl.train.SeriesTrainer>@(src,ed)iUpdateEpisodeFinished(this,ed) (line 17)
In rl.env/AbstractEnv/notifyEpisodeFinished (line 324)
In rl.env.SimulinkEnvWithAgent.executeSimsWrapper/nestedSimFinishedBC (line 222)
In rl.env.SimulinkEnvWithAgent>@(src,ed)nestedSimFinishedBC(ed) (line 232)
In Simulink/SimulationManager/handleSimulationOutputAvailable
In Simulink.SimulationManager>@(varargin)obj.handleSimulationOutputAvailable(varargin{:})
In MultiSim.internal/SimulationRunnerSerial/executeImplSingle
In MultiSim.internal/SimulationRunnerSerial/executeImpl
In Simulink/SimulationManager/executeSims
In Simulink/SimulationManagerEngine/executeSims
In rl.env/SimulinkEnvWithAgent/executeSimsWrapper (line 244)
In rl.env/SimulinkEnvWithAgent/simWrapper (line 267)
In rl.env/SimulinkEnvWithAgent/simWithPolicyImpl (line 424)
In rl.env/AbstractEnv/simWithPolicy (line 82)
In rl.task/SeriesTrainTask/runImpl (line 33)
In rl.task/Task/run (line 21)
In rl.task/TaskSpec/internal_run (line 166)
In rl.task/TaskSpec/runDirect (line 170)
In rl.task/TaskSpec/runScalarTask (line 194)
In rl.task/TaskSpec/run (line 69)
In rl.train/SeriesTrainer/run (line 24)
In rl.train/TrainingManager/train (line 421)
In rl.train/TrainingManager/run (line 211)
In rl.agent.AbstractAgent/train (line 78)
The disk that I am running it on still has 100 GB of space. What is causing this issue?
5 Comments
Stephan
on 7 Dec 2020
Are there any saved agents or is the directory empty?
Tech Logg Ding
on 10 Dec 2020
Emmanouil Tzorakoleftherakis
on 11 Dec 2020
Can you create a technical support case? This is strange.
Aside from that, is there a reason you are saving the experience buffer in all these agents? Typically, saving the experience buffer is helpful if you want to begin training from that specific point in time. Otherwise you don't really need it for inference
Tech Logg Ding
on 12 Dec 2020
Hasan Khanzada
on 13 Apr 2022
Your problem is solved ? because i am having the same issue as you were.
Answers (0)
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