问无法将经过训练的模型部署到现有AKS计算目标
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Stack Overflow用户

提问于 2019-02-20 23:15:26

回答 3查看 885关注 0票数 2

我有一个模型是在Azure机器学习服务上的机器学习计算上训练的。已注册的模型已经存在于我的工作区中，我想将其部署到我之前在工作区中提供的一个预先存在的AKS实例中。我能够成功配置和注册容器镜像：

# retrieve cloud representations of the models
rf = Model(workspace=ws, name='pumps_rf')
le = Model(workspace=ws, name='pumps_le')
ohc = Model(workspace=ws, name='pumps_ohc')
print(rf); print(le); print(ohc)

<azureml.core.model.Model object at 0x7f66ab3b1f98>
<azureml.core.model.Model object at 0x7f66ab7e49b0>
<azureml.core.model.Model object at 0x7f66ab85e710>

package_list = [
  'category-encoders==1.3.0',
  'numpy==1.15.0',
  'pandas==0.24.1',
  'scikit-learn==0.20.2']

# Conda environment configuration
myenv = CondaDependencies.create(pip_packages=package_list)
conda_yml = 'file:'+os.getcwd()+'/myenv.yml'

with open(conda_yml,"w") as f:
    f.write(myenv.serialize_to_string())

配置和注册镜像工作：

# Image configuration
image_config = ContainerImage.image_configuration(execution_script='score.py', 
                                                  runtime='python', 
                                                  conda_file='myenv.yml',
                                                  description='Pumps Random Forest model')


# Register the image from the image configuration
# to Azure Container Registry
image = ContainerImage.create(name = Config.IMAGE_NAME, 
                              models = [rf, le, ohc],
                              image_config = image_config,
                              workspace = ws)

Creating image
Running....................
SucceededImage creation operation finished for image pumpsrfimage:2, operation "Succeeded"

附加到现有群集也可以：

# Attach the cluster to your workgroup
attach_config = AksCompute.attach_configuration(resource_group = Config.RESOURCE_GROUP,
                                                cluster_name = Config.DEPLOY_COMPUTE)
aks_target = ComputeTarget.attach(workspace=ws, 
                                  name=Config.DEPLOY_COMPUTE, 
                                  attach_configuration=attach_config)

# Wait for the operation to complete
aks_target.wait_for_completion(True)
SucceededProvisioning operation finished, operation "Succeeded"

但是，当我尝试将映像部署到现有集群时，它会失败，并显示WebserviceException。

# Set configuration and service name
aks_config = AksWebservice.deploy_configuration()

# Deploy from image
service = Webservice.deploy_from_image(workspace = ws,
                                       name = 'pumps-aks-service-1' ,
                                       image = image,
                                       deployment_config = aks_config,
                                       deployment_target = aks_target)
# Wait for the deployment to complete
service.wait_for_deployment(show_output = True)
print(service.state)

WebserviceException: Unable to create service with image pumpsrfimage:1 in non "Succeeded" creation state.
---------------------------------------------------------------------------
WebserviceException                       Traceback (most recent call last)
<command-201219424688503> in <module>()
      7                                        image = image,
      8                                        deployment_config = aks_config,
----> 9                                        deployment_target = aks_target)
     10 # Wait for the deployment to complete
     11 service.wait_for_deployment(show_output = True)

/databricks/python/lib/python3.5/site-packages/azureml/core/webservice/webservice.py in deploy_from_image(workspace, name, image, deployment_config, deployment_target)
    284                         return child._deploy(workspace, name, image, deployment_config, deployment_target)
    285 
--> 286         return deployment_config._webservice_type._deploy(workspace, name, image, deployment_config, deployment_target)
    287 
    288     @staticmethod

/databricks/python/lib/python3.5/site-packages/azureml/core/webservice/aks.py in _deploy(workspace, name, image, deployment_config, deployment_target)

对如何解决这个问题有什么想法吗？我在Databricks笔记本上写代码。此外，我可以使用Azure Portal创建和部署集群，没有问题，所以这似乎是我的代码/Python SDK或Databricks与AMLS的工作方式的问题。

更新:我能够使用Azure Portal将我的镜像部署到AKS，was服务工作正常。这意味着问题存在于Databricks、Azureml Python SDK和Machine Learning Service之间。

更新2:我正在与微软合作来解决这个问题。一旦我们有了解决方案就会报告。

azure

azure-aks

azure-machine-learning-service

回答 3

Stack Overflow用户

回答已采纳

发布于 2019-03-07 20:22:05

在我的初始代码中，当创建图像时，我没有使用：

image.wait_for_creation(show_output=True)

因此，我在创建映像之前调用了CreateImage和DeployImage，但出现了错误。不敢相信有这么简单..。

更新的镜像创建片段：

# Register the image from the image configuration
# to Azure Container Registry
image = ContainerImage.create(name = Config.IMAGE_NAME, 
                              models = [rf, le, ohc],
                              image_config = image_config,
                              workspace = ws)

image.wait_for_creation(show_output=True)