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Select Save Job Log, and specify the OBS bucket for saving job logs. Change the values of the parameters in bold as needed in the following script.
Before writing dirty data, create an OBS link. You can view the data on OBS later. Retain the default value No, meaning dirty data is not recorded. Click Save and Run. On the Job Management page, you can view the job execution progress and result.
Before writing dirty data, create an OBS link. You can view the data on OBS later. Retain the default value No, meaning dirty data is not recorded. Click Save and Run. On the Job Management page, you can view the job execution progress and result.
For more logs, check the OBS bucket where the job logs are stored. Search for dependency information in the logs. Search for Classpath: in the logs to check the dependencies.
Contact customer service. 400 CPS.0107 Parameters for upload files to obs is invalid. Parameters for upload files to obs is invalid. Contact customer service. 400 CPS.0108 Upload files to obs failed. Upload files to obs failed.
Table 24 ObsObjInfo Parameter Mandatory Type Description bucket Yes String OBS bucket name location Yes String Region where an OBS bucket is located.
bucket or OBS parallel file system): For an object bucket, set the mount path to /tmp and permission to ReadWriteMany.
Example Request Parse the demo-app-package.zip release task template package stored in the obs://apitest/ directory of the OBS bucket. { "sources": [ { "template_source": { "storage": "obs", "url": "obs://apitest/demo-app-package.zip
string Backup description links list<dict> Backup URL availability_zone string AZ where the backup resides volume_id string Source disk ID of the backup fail_reason string Cause of the backup failure id string Backup ID size int Backup size object_count int Number of objects on OBS
Archive to OBS: Dirty data is stored in OBS and printed in job logs. Do not archive Write Dirty Data Link This parameter is displayed when Dirty Data Policy is set to Archive to OBS.
using a temporary URL generated by the OBS BrowserJS SDK, perform the following steps: Call ObsClient.createSignedUrlSync to generate a signed URL.
\":[\"o-bf966fe82ebb4d35d68b791729228788/r-001ebf32880a13eabfc8e1c37eee3ae9/ou-0dbfffe92fd92ddb35feff9b4079459c\"]},\"Action\":[\"SMN:Publish\",\"SMN:QueryTopicDetail\"],\"Resource\":\"{topic_urn}\"},{\"Sid\":\"__service_pub_0\",\"Effect\":\"Allow\",\"Principal\":{\"Service\":[\"obs
It is an OBS address where the function code package is stored. projectID Yes No Project ID. handler Yes Yes Function handler. runtime Yes No Execution environment.
Others Additional charges will apply if other cloud services, such as OBS and SMN, are used with FunctionGraph. Billing modes of involved services The billing modes of other cloud services are different. For details, see Pricing Details.
an Image Purchasing an EVS Disk Using DIS Using DIS Flume Plugin to Upload and Download Data Using DIS Logstash Plugin to Upload and Download Data Using SparkStraming SDK to Download Data Configuring Security Group Rules Managing a Dump Task Creating a Dump Task Dumping Data to OBS
OPENMPI_HOST_FILE_PATH} \ -mca plm_rsh_args "-p ${SSHD_PORT}" \ -tune ${TUNE_ENV_FILE} \ ${OPENMPI_BIND_ARGS} \ ${OPENMPI_X_ARGS} \ ${OPENMPI_MCA_ARGS} \ ${OPENMPI_EXTRA_ARGS} \ python /home/ma-user/user-job-dir/gpu-train/train.py --datasets=obs
Export images to your OBS bucket.
Deploying the predictor in Deploying a Real-Time Service is to deploy the model file stored in OBS to the container provided by the Service Deployment module. The environment specifications (such as CPU and GPU specifications) are determined by configs parameters of predictor.
Supported AI Engines for ModelArts Inference If you import a model from a template or OBS to create an AI application, the following AI engines and versions are supported.
Figure 2 Deploying code If you deploy code by uploading a local ZIP file, ensure that the region selected for creating the function is the same as that selected for creating an OBS bucket. You can modify the code and click Deploy to deploy the code again.
