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When a CV2 Model Package Is Used to Deploy a Real-Time Service Service Is Consistently Being Deployed A Started Service Is Intermittently in the Alarm State Failed to Deploy a Service and Error "No Module named XXX" Occurred Insufficient Permission to or Unavailable Input/Output OBS
path of the training job output file log_url String OBS URL of the logs of a training job.
History How Do I Upload Data to OBS? Which AI Frameworks Does ModelArts Support? How Does ModelArts Use Tags to Manage Resources by Group? How Do I View ModelArts Expenditure Details? What Do I Do If the VS Code Window Is Not Displayed?
In this example, the installation package has been uploaded to obs://cnnorth4-test/codes/mox_benchmarks/apex-master/.
For example, the OBS path specified by Code Directory contains model files and the pip-requirements.txt file.
Input Path OBS path to the input data in the batch service. Output Path OBS path to the output data in the batch service. Model Name & Version Name and version of the model used by the batch service. Advanced Log Management This feature is disabled by default.
Critical Table 7 Events for dynamic OBS mounting Event Description Severity DynamicMountStorage The OBS storage is mounted. Major DynamicUnmountStorage The OBS storage is unmounted.
Data mounting If the collected logs are stored on OBS, mount the log data in OBS using the rclone tool. Download and install rclone. Configure the credentials required for accessing OBS. # Hard-coded or plaintext AK/SK is risky.
String Error code. error_msg String Error message. file_statistics FileCopyProgress object File replication progress finished_file_count Long Number of files that have been transferred. finished_file_size Long Size of the file that has been transferred, in bytes. import_path String OBS
# Define the input OBS object. obs_data = wf.data.OBSPlaceholder(name="obs_placeholder_name", object_type="directory") # Use JobStep to define a training phase, and use OBS to store the output. job_step = wf.steps.JobStep( name="training_job", # Name of a training phase.
Code Directory Select the OBS directory where the training code file is stored. Dynamic routing acceleration improves network communication by adjusting the rank ID. To prevent communication issues, unify the rank usage in the code.
ModelArts data management provides the following functions for you to obtain high-quality AI data: Data acquisition Allows you to import data from OBS and MRS. Provides 18+ data augmentation operators to increase data volume for training.
Feature Description Phase Document 1 Access key authorization discontinued Certain ModelArts functions require access to OBS, SWR, and IEF. Before using ModelArts, ensure your account has been authorized to access these services.
Input Path OBS path to the input data in the batch service. Output Path OBS path to the output data in the batch service. AI Application Name & Version Name and version of the AI application used by the batch service. Advanced Log Management This function is disabled by default.
Feature Description Phase Document 1 Access key authorization discontinued Certain ModelArts functions require access to OBS, SWR, and IEF. Before using ModelArts, ensure your account has been authorized to access these services.
For example, you can grant access permission on an OBS bucket to a tenant for model management. Internal resource authorization ModelArts inference supports fine-grained permission control.
# Define the input OBS object. obs_data = wf.data.OBSPlaceholder(name="obs_placeholder_name", object_type="directory") # Use JobStep to define a training phase, and use OBS to store the output. job_step_1 = wf.steps.JobStep( name="training_job_1", # Name of a training phase
Permanent logs: These logs are dumped to your OBS bucket. When creating a training job, you can enable persistent log saving and set a job log path for dumping. Figure 1 Enabling Persistent Log Saving Real-time logs and historical logs have no difference in content.
Obtain the detailed OBS path next to Output Path, switch to the path and obtain the batch service prediction results, including the prediction result file and the AI application prediction result.
Prerequisites The training job has been successfully executed, and the model has been stored in the OBS directory where the training output is stored (the input parameter is train_url).
