Chr*_*ell 1 azure-machine-learning-service
我正在尝试使用新的 ML 服务 SDK 将映像部署到 Azure 容器实例中的 Web 服务。该Webservice.deploy_from_image方法失败并显示以下消息:
> Traceback (most recent call last): File
> "c:/Users/chrcam/git/amlIrisClassification/deploy_iris_to_aci.py",
> line 18, in <module>
> workspace = ws) File "C:\Users\chrcam\AppData\Local\Programs\Python\Python36\lib\site-packages\azureml\core\webservice\webservice.py",
> line 258, in deploy_from_image
> return deployment_config._webservice_type._deploy(workspace, name, image, deployment_config) File
> "C:\Users\chrcam\AppData\Local\Programs\Python\Python36\lib\site-packages\azureml\core\webservice\aci.py",
> line 121, in _deploy
> deployment_config.validate_image(image) File "C:\Users\chrcam\AppData\Local\Programs\Python\Python36\lib\site-packages\azureml\core\webservice\webservice.py",
> line 883, in validate_image
> if image.creation_state != 'Succeeded': AttributeError: 'str' object has no attribute 'creation_state'
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我从 SDK 的 1.68 版本开始,然后以相同的结果升级到 1.80。
模型和图像都在我的工作区中注册。
代码相当简单。任何反馈或方向都会有所帮助。
from azureml.core import Workspace
from azureml.core.webservice import Webservice
from azureml.core.webservice import AciWebservice
ws = Workspace.from_config()
image_name = 'irisimage'
service_name = 'aciiris'
aciconfig = AciWebservice.deploy_configuration(cpu_cores = 1,
memory_gb = 1,
tags = {"data": "iris", "type": "classification"},
description = 'Iris Classification')
service = Webservice.deploy_from_image(deployment_config = aciconfig,
image = image_name,
name = service_name,
workspace = ws)
service.wait_for_deployment(show_output = True)
print(service.state)
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我想到了。也许这会帮助别人。deploy_from_image 方法需要一个 Image 对象,而不是图像名称作为参数。错误消息具有误导性,我认为 SDK 中可能存在错误。
这是更新后的代码:
from azureml.core import Workspace
from azureml.core import Image
from azureml.core.webservice import Webservice
from azureml.core.webservice import AciWebservice
ws = Workspace.from_config()
image_name = 'irisimage'
service_name = 'aciiris'
image = Image(name=image_name, workspace=ws)
aciconfig = AciWebservice.deploy_configuration(cpu_cores = 1,
memory_gb = 1,
tags = {"data": "iris", "type": "classification"},
description = 'Iris Classification')
service = Webservice.deploy_from_image(deployment_config = aciconfig,
image = image,
name = service_name,
workspace = ws)
service.wait_for_deployment(show_output = True)
print(service.state)
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