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Table 2 Data source types Type Example OBS "source":"s3://path-to-jpg" Content "source":"content://I love machine learning" Table 3 annotation objects Parameter Mandatory Description type Yes Label type.
Possible Causes When a model is imported through OBS, ModelArts copies all files and folders in the specified OBS directory to a path specified in the image. You can obtain the path in the image by using self.model_path.
Parent topic: OBS Management
Solution Check whether the ModelArts project and the created OBS bucket are in the same region. Check the region where the created OBS bucket is located. Log in to OBS Console. On the Object Storage Service page, to search for a bucket, enter a keyword in Bucket Name.
Large files (files larger than 100 MB) Use OBS to upload large files. To do so, use OBS Browser to upload a local file to an OBS bucket and use ModelArts SDK to download the file from OBS to a notebook instance.
trained model or other training script data is stored. obs_path: OBS path.
Using the SDK to Debug a Multi-Node Distributed Training Job Replace the OBS paths in the debugging code with your OBS paths. PyTorch is used to write debugging code in this document. The process is the same for different AI frameworks.
Uploading Data to OBS In this section, the OBS console is used to upload data. Upload files to OBS according to the following specifications: The name of files cannot contain plus signs (+), spaces, or tabs.
You can obtain the OBS path set for Output Dataset Path. Log in to the OBS management console and locate the version directory from the obtained OBS path to obtain the labeling result of the dataset.
Log in to OBS Console and create a bucket in the same region as ModelArts. If an available bucket exists, ensure that the OBS bucket and ModelArts are in the same region. Upload the local data to the OBS bucket.
Notebook instance with OBS storage (old-version notebooks) For this type of notebook instances, the files uploaded to JupyterLab are stored in the OBS path specified during the instance creation by default.
Parsing a Manifest File Parse a manifest file in either a local or OBS path.
Uploading Data to OBS In this section, the OBS console is used to upload data.
Upload files to OBS according to the following specifications: The OBS path of the predictive analytics projects must comply with the following rules: The OBS path of the input data must redirect to the data files.
You have created an OBS bucket. The OBS bucket and ModelArts are in the same region and you can operate the bucket. Import Operation Both file and table data can be uploaded from local files. The data uploaded from local files should be stored in an OBS directory.
You have created an OBS bucket. The OBS bucket and ModelArts are in the same region and you can operate the bucket. Import Operation Both file and table data can be uploaded from local files. The data uploaded from local files should be stored in an OBS directory.
However, OBS bills you for the storage space used for storing the datasets. You are advised to go to the OBS management console and delete the stored data and OBS buckets to stop billing. Parent topic: Billing FAQs
If an available bucket exists, ensure that the OBS bucket and ModelArts are in the same region. Upload the local data to the OBS bucket. If you have a large amount of data, use OBS Browser+ to upload data or folders.
Parsing a Pascal VOC File Parse an XML file in either a local or OBS path. If an OBS path is used, a session is required.
Creating a Dataset Import Task You can import new data from OBS through an OBS path or a manifest file. dataset.import_data(path=None, anntation_config=None, **kwargs) Table 1 lists the import modes supported by datasets.
