Obtaining the Model List¶
Sample Code¶
In ModelArts notebook, you do not need to enter authentication parameters for session authentication. For details about session authentication of other development environments, see Session Authentication.
Scenario 1: Query all models of a user.
from modelarts.session import Session
from modelarts.model import Model
session = Session()
model_list = Model.get_model_list(session)
Scenario 2: Query a model based on the search criteria.
from modelarts.session import Session
from modelarts.model import Model
session = Session()
model_list = Model.get_model_list(session, model_status="published", model_name="digit", order="desc")
Parameter Description¶
Parameter | Mandatory | Type | Description |
|---|---|---|---|
model_name | No | String | Model name. Fuzzy match is supported. |
model_version | No | String | Model version |
model_status | No | String | Model status. The value can be publishing, published, or failed. Obtain jobs based on their statuses. |
description | No | String | Description. Fuzzy match is supported. |
offset | No | Integer | Index of the page to be queried. Default value: 0 |
limit | No | Integer | Maximum number of records returned on each page. Default value: 280 |
sort_by | No | String | Sorting mode. The value can be create_at, model_version, or model_size. Default value: create_at |
order | No | String | Sorting order. The value can be asc or desc, indicating the ascending or descending order. Default value: desc |
workspace_id | No | String | Workspace ID. Default value: 0 |
Parameter | Type | Description |
|---|---|---|
total_count | Integer | Total number of models that meet the search criteria when no paging is implemented |
count | Integer | Number of models |
models | model array | Model metadata |
Parameter | Type | Description |
|---|---|---|
model_id | String | Model ID |
model_name | String | Model name |
model_version | String | Model version |
model_type | String | Model type. The value can be TensorFlow, MXNet, Spark_MLlib, Scikit_Learn, XGBoost, MindSpore, Image, or PyTorch. |
model_size | Long | Model size, in bytes |
tenant | String | Tenant to whom a model belongs |
project | String | Project to which a model belongs |
owner | String | User to whom a model belongs |
create_at | Long | Time when a model is created, in milliseconds calculated from 1970.1.1 0:0:0 UTC |
description | String | Model description |
source_type | String | Model source type. This parameter is valid only when the model is deployed by an ExeML project. The value is auto. |