检测到您已登录华为云国际站账号，为了您更好的体验，建议您访问国际站服务网站 https://www.huaweicloud.com/intl/zh-cn
不再显示此消息
检测到您已登录华为云国际站账号，为了您更好的体验，建议您访问国际站服务网站 https://www.huaweicloud.com/intl/zh-cn
不再显示此消息
OBS Catalog: The storage structure supports Images and labels. Images and labels: The structure varies depending on the scenario type. The following shows the directory structure in the image classification scenario.
By default, this parameter is left blank. src_path Yes String OBS path of the input data of a batch job dest_path Yes String OBS path of the output data of a batch job req_uri Yes String Inference API called in a batch task, that is, the RESTful API exposed in the model image.
General-purpose Intel CPU flavor, ideal for rapid data exploration and experiments", "feature" : "NOTEBOOK", "free" : false, "id" : "modelarts.vm.cpu.2u", "memory" : 8388608, "name" : "CPU: 2 vCPUs 8 GB", "sold_out" : false, "storages" : [ "EVS", "OBSFS", "EFS", "OBS
15099239923, "resource_id": "4787c885-e18d-4ef1-aa12-c4ed0c364b27", "duration": 1502323, "job_desc": "This is a visualization job", "service_url": "https://console.huaweicloud.com/modelarts/tensoarbod/xxxx/111", "train_url": "/obs
Not Using Hard-coded Credentials During Development If you want to develop an algorithm and publish it to the production environment in ModelArts Standard Notebook, you shall check the password, AK/SK, database connection, OBS connection, and SWR connection information used in the
However, the original data in the dataset and the labeled data that has been accepted are still stored in the corresponding OBS bucket. Parent topic: Team Labeling
Currently, only the value 0 is supported, indicating that the OBS file size is limited. import_data Boolean Whether to import data.
Enter an existing OBS path in the format of /OBS bucket name/Folder path/. Dataset object: Enter the dataset name and version number. Training flavor: Configure GPU resources since the algorithm in this example can run only on GPUs.
The work directory of a table dataset cannot be an OBS path in a KMS-encrypted bucket. Only one data source can be imported at a time. dataset_name Yes String Dataset name. The value contains 1 to 100 characters.
# 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.
Currently, only the value 0 is supported, indicating that the OBS file size is limited. import_data Boolean Whether to import data.
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.
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
Pay-per-use Yearly/Monthly Creating an OBS bucket is free of charge. You pay only for the storage capacity and duration you actually use. For details, see Object Storage Price Calculator.
The options are as follows: DIR: Data is exported to OBS (default value).
When creating an algorithm, ensure that the names of files and folders in the OBS bucket where the algorithm code is stored are unique. Otherwise, the algorithm may fail to be published. If the algorithm is published, the code fails to be opened.
Supported AI Engines for Inference If you import a preset image from a template or OBS to create a model, you can select the AI engines and versions in the table below.
Prerequisites The OBS directory you use and ModelArts are in the same region. Procedure Log in to the ModelArts console and choose Model Management in the navigation pane on the left. Click Create Model. Configure parameters. Set basic information about the model.
OBS path to the output data of a batch job instance_count Yes Integer Common parameter. Number of instances deployed in a model. The maximum number of instances is 128.
