如何使用本地包创建 azure 机器学习评分图像

Question

我将 pkl 包保存在我的 azure devops 存储库中

使用下面的代码在工作区中搜索包。如何提供存储库中保存的包

 ws = Workspace.get(
         name=workspace_name,
         subscription_id=subscription_id,
        resource_group=resource_group,
        auth=cli_auth)

image_config = ContainerImage.image_configuration(
    execution_script="score.py",
    runtime="python-slim",
    conda_file="conda.yml",
    description="Image with ridge regression model",
    tags={"area": "ml", "type": "dev"},
)

image = Image.create(
    name=image_name,  models=[model], image_config=image_config, workspace=ws
)

image.wait_for_creation(show_output=True)

if image.creation_state != "Succeeded":
    raise Exception("Image creation status: {image.creation_state}")

print(
    "{}(v.{} [{}]) stored at {} with build log {}".format(
        image.name,
        image.version,
        image.creation_state,
        image.image_location,
        image.image_build_log_uri,
    )
)

# Writing the image details to /aml_config/image.json
image_json = {}
image_json["image_name"] = image.name
image_json["image_version"] = image.version
image_json["image_location"] = image.image_location
with open("aml_config/image.json", "w") as outfile:
    json.dump(image_json, outfile)

我试图提供模型的路径，但它失败说找不到包

型号 = $(System.DefaultWorkingDirectory)/package_model.pkl

Answer 1

注册型号：通过调用 Model.register().

将文件或文件夹注册为模型

除了模型文件本身的内容之外，您注册的模型还将存储模型元数据——模型描述、标签和框架信息——这在您的工作区中管理和部署模型时非常有用。例如，使用标签，您可以对模型进行分类并在工作区中列出模型时应用过滤器。

model = Model.register(workspace=ws,
                       model_name='',                # Name of the registered model in your workspace.
                       model_path='',  # Local file to upload and register as a model.
                       model_framework=Model.Framework.SCIKITLEARN,  # Framework used to create the model.
                       model_framework_version=sklearn.__version__,  # Version of scikit-learn used to create the model.
                       sample_input_dataset=input_dataset,
                       sample_output_dataset=output_dataset,
                       resource_configuration=ResourceConfiguration(cpu=1, memory_in_gb=0.5),
                       description='Ridge regression model to predict diabetes progression.',
                       tags={'area': 'diabetes', 'type': 'regression'})

print('Name:', model.name)
print('Version:', model.version)

将机器学习模型部署到 Azure：https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-and-where?tabs=python

远程模型部署疑难解答请遵循document。

如何使用本地包创建 azure 机器学习评分图像

how create azure machine learning scoring image using local package

machine-learning

azure

azure-machine-learning-studio

azure-machine-learning-service