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AI Gallery stores file assets in official OBS buckets. AI Gallery stores image assets in official SWR repositories. AI Gallery stores personal information of users in databases. AI Gallery encrypts sensitive personal information, such as mobile numbers and emails, in databases.
To quickly obtain the latest data in the OBS bucket, on the All or Unlabeled tab page of the dataset details page, click Synchronize Data Source to add data from OBS to the dataset. Filtering Data On the Dashboard page of the dataset, click Label in the upper right corner.
#mox.file.copy_parallel(args.data_url, local_data_path) ... # Upload the local container data to the OBS path.
Symptom: After the labeled data is uploaded to OBS and synchronized, the data is displayed as unlabeled. Possible causes: Automatic encryption is enabled in the OBS bucket. Solution: Create an OBS bucket and upload data again, or disable bucket encryption and upload data again.
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.
Debugging a Training Job Debugging a Model 2020-04-10 Added the following sections: OBS Management: Added OBS-related operation guide. 2019-08-20 This is the second official release. Added the following sections: Training Management: Added the local training function.
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
Creating a version When creating a new version, you can select a meta model only from a ModelArts training job, OBS, model template, or custom image. You cannot create a version from the original ExeML project. Deleting a model or its version Parent topic: Tips
Upload the training script mindspore-verification.py to obs://test-modelarts/ascend/demo-code/ in the OBS bucket. Upload the five Ascend startup scripts to the obs://test-modelarts/ascend/demo-code/run_ascend/ folder in the OBS bucket.
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
"obs://hard_example_path/Data/be462ea9c5abc09f_checked.xml", "type": "modelarts/object_detection", "annotation-format": "PASCAL VOC", "annotated-by": "modelarts/hard_example_algo" } ] } Parent topic: Built-in Operators
Symptom: After the labeled data is uploaded to OBS and synchronized, the data is displayed as unlabeled. Possible causes: Automatic encryption is enabled in the OBS bucket. Solution: Create an OBS bucket and upload data again, or disable bucket encryption and upload data again.
Data and its labeling information are still stored in the OBS directory. However, this affects version management. Exercise caution when performing this operation. Parent topic: Preparing and Processing Data
Select the OBS directory where the training code file is stored. Upload code to the OBS bucket beforehand. The total size of files in the directory cannot exceed 5 GB, the number of files cannot exceed 1,000, and the folder depth cannot exceed 32.
Directory Structure of Dataset Versions Datasets are managed based on OBS directories. After a new version is published, the directory is generated based on the new version in the output dataset path. Take an image classification dataset as an example.
Prerequisites The training job has been executed, and the model has been stored in the OBS directory where the training output is stored (the input parameter is train_url).
Name: name of the new dataset Storage Path: input path of the new dataset, that is, the OBS path where the data to be exported is stored Output Path: output path of the new dataset, that is, the output path after labeling is complete The output path cannot be the same as the storage
Only OBS parallel file systems are supported. Source Path: Select the storage path of the parallel file. A cross-region OBS parallel file system cannot be selected. Mount Path: Enter the mount path of the container, for example, /obs-mount/. Select a new directory.
To quickly obtain the latest data in the OBS bucket, on the All or Unlabeled tab page of the dataset details page, click Synchronize Data Source to add data from OBS to the dataset.
path of the training job output file log_url String OBS URL of the logs of a training job.
