out-of-memory

问题 I am using airflow to schedule a pipeline that will result in training a scikitlearn model with ai platform. I use this DAG to train it with models.DAG(JOB_NAME, schedule_interval=None, default_args=default_args) as dag: # Tasks definition training_op = MLEngineTrainingOperator( task_id='submit_job_for_training', project_id=PROJECT, job_id=job_id, package_uris=[os.path.join(TRAINER_BIN)], training_python_module=TRAINER_MODULE, runtime_version=RUNTIME_VERSION, region='europe-west1', training

问题 chrome invoked oom-killer: gfp_mask=0xd0, order=0, oom_score_adj=300 I'm getting the above error while testing with headless chrome browser + Selenium. 回答1: This error message... chrome invoked oom-killer: gfp_mask=0xd0, order=0, oom_score_adj=300 ...implies that the ChromeDriver controlled Browsing Context i.e. Chrome Browser invoked the OOM Killer due to out-of-memory error. Out of Memory Out of Memory error messages can appear when you attempt to start new programs or you try to use

问题 When application is in use for few minutes then it slowly increases the Used memory value and decreases Free memory value. Application get very slow after few minutes. Why isn't it releasing the memory. System configuration : CPU : Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz (No. of processors : 4 / No. of cpu cores : 8) RAM : 30 GB OS : CentOS-7 Application configuration : java version "1.8.0_171" -- build 1.8.0_171-b11 apache-tomcat-7.0.55 Tomcat setting Free -h command Top command . .

问题 I have a very big Problem with our App. We need much space for Bitmap transformation, but directly at Startup (of the App) most of the Memory gets Allocated with unknown Stuff... Below you can find the Console Output from Xamarin Studio. What could possibly trigger such big allocations? The App is tested on different devices, the Output below is from the Worst One (Samsung Galaxy S3) This is my OnCreate of MainActivity: protected override void OnCreate(Bundle bundle) { base.OnCreate(bundle);

问题 I've created a WebApp for a Tomcat8 Server. It is a small webbased game. Since I've switched from flatfiles to MySQL I have a lot of problems with javax.json builder. Here the part of my code: public void saveUserResearch(){ MySQLTable t = SpaceWar.instance().getUserResearchTable(); JsonObjectBuilder mainBuilder = Json.createObjectBuilder(); JsonObjectBuilder subBuilder = Json.createObjectBuilder(); for(UserResearch r : getResearchList()){ int index = r.getIndex(); subBuilder = Json

问题 I've created a WebApp for a Tomcat8 Server. It is a small webbased game. Since I've switched from flatfiles to MySQL I have a lot of problems with javax.json builder. Here the part of my code: public void saveUserResearch(){ MySQLTable t = SpaceWar.instance().getUserResearchTable(); JsonObjectBuilder mainBuilder = Json.createObjectBuilder(); JsonObjectBuilder subBuilder = Json.createObjectBuilder(); for(UserResearch r : getResearchList()){ int index = r.getIndex(); subBuilder = Json

问题 I've spent the morning reading through page after page of StackOverflow posts about this exact error, but the root cause of their problems always seems to be either 1) they have very large images which need to be down sampled or 2) they are suffering after one or more device rotations which cause the activity to be destroyed and recreated several times. I'm getting this error (only very rarely), but my app only allows portrait orientation so no rotations are possible and all of my images are

问题 I've spent the morning reading through page after page of StackOverflow posts about this exact error, but the root cause of their problems always seems to be either 1) they have very large images which need to be down sampled or 2) they are suffering after one or more device rotations which cause the activity to be destroyed and recreated several times. I'm getting this error (only very rarely), but my app only allows portrait orientation so no rotations are possible and all of my images are

问题 I'm diving into LSTM RNN with Keras and Theano backend. While trying to use lstm examples from keras' repo whole code of lstm_text_generation.py on github, I've got one thing that isn't pretty clear to me: the way it's vectorizing the input data (text characters): # cut the text in semi-redundant sequences of maxlen characters maxlen = 40 step = 3 sentences = [] next_chars = [] for i in range(0, len(text) - maxlen, step): sentences.append(text[i: i + maxlen]) next_chars.append(text[i + maxlen

问题 I'm diving into LSTM RNN with Keras and Theano backend. While trying to use lstm examples from keras' repo whole code of lstm_text_generation.py on github, I've got one thing that isn't pretty clear to me: the way it's vectorizing the input data (text characters): # cut the text in semi-redundant sequences of maxlen characters maxlen = 40 step = 3 sentences = [] next_chars = [] for i in range(0, len(text) - maxlen, step): sentences.append(text[i: i + maxlen]) next_chars.append(text[i + maxlen