如何在Azure ML Service中注册本地训练的机器学习模型？ [英] How can I register in Azure ML Service a machine learning model trained locally?

问题描述

我正在尝试

有什么方法可以注册然后部署一个预训练的腌制模式（如果有意义的话，无需提交运行）？

解决方案

可以使用 Model.register ，无需使用 run 对象

  model = Model.register （model_name ='my_model'，model_path ='my_model.pkl'，工作区= ws）
  

部署人员可以按照 Azure ML服务文档。

I am trying out Azure Machine Learning Service for ML deployment.

I have already trained a model on a compute VM and saved it as pickle, and now would like to deploy it (I am using Python on Azure notebooks for the purpose as of now).

From the guide, it looks like I need to I need a run object to be existing in my session to execute the "model registration" step:

# register model 
model = run.register_model(model_name='my_model', model_path='outputs/my_model.pkl')
print(model.name, model.id, model.version, sep = '\t')

However, I haven't created any run object as I haven't executed any experiment for training, I am just starting off with my pickled model.

I also tried to register a model by uploading it via the Azure Portal (see screenshot below), but (as the model file is quite large, I assume) it fails with a ajax error 413. as in Unable to register an ONNX model in azure machine learning service workspace.

Is there any way to register and then deploy a pretrained pickled mode (without the need of submitting a run, if that makes sense)?

解决方案

Model registration can be done with Model.register, without the need of using a run object

model = Model.register(model_name='my_model', model_path='my_model.pkl', workspace = ws)

for the deployment one can follow steps as outlined in the Azure ML service doc.

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