将模型管理升级到 SDK v2
本文比较 SDK v1 和 SDK v2 中的方案。
创建模型
SDK v1
import urllib.request from azureml.core.model import Model # Register model model = Model.register(ws, model_name="local-file-example", model_path="mlflow-model/model.pkl")
SDK v2
from azure.ai.ml.entities import Model from azure.ai.ml.constants import AssetTypes file_model = Model( path="mlflow-model/model.pkl", type=AssetTypes.CUSTOM_MODEL, name="local-file-example", description="Model created from local file." ) ml_client.models.create_or_update(file_model)
在试验/作业中使用模型
SDK v1
model = run.register_model(model_name='run-model-example', model_path='outputs/model/') print(model.name, model.id, model.version, sep='\t')
SDK v2
from azure.ai.ml.entities import Model from azure.ai.ml.constants import AssetTypes run_model = Model( path="azureml://jobs/$RUN_ID/outputs/artifacts/paths/model/", name="run-model-example", description="Model created from run.", type=AssetTypes.CUSTOM_MODEL ) ml_client.models.create_or_update(run_model)
有关模型对详细信息,请参阅在 Azure 机器学习中使用模型。
SDK v1 和 SDK v2 中关键功能的映射
SDK v1 中的功能 | SDK v2 中的粗略映射 |
---|---|
Model.register | ml_client.models.create_or_update |
run.register_model | ml_client.models.create_or_update |
Model.deploy | ml_client.begin_create_or_update(blue_deployment) |
后续步骤
有关详细信息,请参阅此处的文档: