superstatus.blogg.se

Somebody more experienced than me kindly help io / not-ready :NoExecute for 300 s node. Why I am getting this - Tolerations : node. Normal Scheduled 67 s default-scheduler Successfully assigned default/sv-p remier-5cc8f599f6-9lrtq to docker-desktop Normal Pulling 66 s kubelet, docker-desktop Pulling image "gcr.io/proto/premiercore1:latest" Normal Pulled 64 s kubelet, docker-desktop Successfully pulled image "gcr.io/proto/premiercore1:latest" Normal Created 64 s kubelet, docker-desktop Created container sv-p remier Normal Started 64 s kubelet, docker-desktop Started container sv-p remier Tolerations: / not -ready:NoExecute for 300 s Type: Secret (a volume populated by a Secret) var/secrets/google from google-cloud- key (rw) var/ run /secrets/kubernetes.io/serviceaccount from default-token-s4jgd (ro) GOOGLE_APPLICATION_CREDENTIALS: /var/secrets/google/ key. While true do echo Done Deploying sv-p remier sleep 3600 done State: Running Image: gcr.io/proto/p remiercore1:latest Image ID: docker-pullable://gcr.io/proto/p Port: 4343 /TCP Priority: 0 Node: docker-desktop/ 192.168.65.3 Start Time: Tue, 19 : 04 : 21 + 0530 Labels: app=sv-p remier pod-template-hash= 5 cc8f599f6Ĭontrolled By: ReplicaSet/sv-p remier-5cc8f599f6 Containers: Kubectl describe pods sv-premier-5cc8f599f6-9lrtq Name : sv-p remier-5cc8f599f6-9lrtq Namespace: default Kubectl get pods NAME READY STATUS RESTARTS AGE I created deployment as - kubectl apply -f deployment.yaml name : google-cloud- key mountPath: /var/secrets/google name : sv-p remier image: gcr.io/proto/p remiercore1:latest imagePullPolicy: AlwaysĪrgs: I want to create Kubernetes Cluster on my local system(mac). Multim odal group regularization.I'm new to Kubernetes and I'm struggling with few error. That appli es struct ured regularization on the weights based on Multim odal inputs effectively, for which we present a m eth od The second, with mo re feat ures, is slow er but has to run Run, and can effectively pru ne out unlikely can dida te grasps.

The first network has few er feat ures, is fas ter to Wh ere the top de tections from the first a re re-evalua ted by

We present a two-s tep casca ded sys tem with two deep networks, In or der to make de tection fast and robust, First, we need to evalua te a huge num ber ofĬan dida te grasps. We apply a deep learning ap proach to solve this problem, whichĪvoids time-con suming hand- design of feat ures. In an RGB-D view of a sce ne containing objects. We consi der the problem of de tecting robotic grasps rw-r-r- 1 root root 120 Sep 29 17:46 wpa_supplicant.log rw- 1 root root 695K Sep 30 03:06 NetworkManagerĭrwxr-xr-x 2 root root 4.0K Sep 29 17:17 podsĭrwxr-x- 2 root root 20K Sep 29 03:55 qingcloud-flex-volume rw- 1 root root 37G Sep 30 09:51 messages rw- 1 root root 183M Sep 30 09:51 maillog rw-r-r- 1 root root 560K Sep 29 17:46 firewall rw-r-r- 1 root root 39K Sep 29 15:42 dmesg.oldĭrwxr-xr-x 2 root root 4.0K Sep 29 17:12 filebeatĭrwxr-xr-x 2 root root 4.0K Jun 7 21:11 filelog rw- 1 root root 74K Sep 30 03:06 dhclient Kubelet 上报了DiskPressure 状态为true - lastHeartbeatTime: CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS log]# docker psĬONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMESįilesystem Size Used Avail Use% Mounted on