aws / aws/sagemaker-python-sdk
SageMaker Model Cards UI doesn't show Model Cards created using model package details
- 主要语言
- Python
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描述
Describe the bug
When creating a model card using model package details, the model card is created and visible from the CLI but is not visible in the Model Cards section of the UI.
To reproduce
Create a model package details object like below. The code was obtained from the following [AWS article](https://aws.amazon.com/blogs/machine-learning/integrate-amazon-sagemaker-model-cards-with-the-model-registry/).
mp = ModelPackage.from_model_package_arn(
model_package_arn="arn:aws:sagemaker:us-east-2:000000000000:model-package/test-model-cards/7"
)
mc = ModelCard(
name="test-model-card-from-model-package",
model_package_details=mp
)
mc.create()
The output from the create function returns the ARN of the newly created model card i.e. arn:aws:sagemaker:us-east-2:000000000000:model-card/test-model-card-from-model-package' but does not show in the UI.
Expected behavior
The model card should be visible under Governance -> Model cards section of the SageMaker management console UI.
Screenshots or logs
Model card can be found using CLI command aws sagemaker list-model-cards
list_model_cards_output
System information
A description of your system. Please provide:
SageMaker Python SDK version: 2.184.0
Framework name (eg. PyTorch) or algorithm (eg. KMeans): SKLearn
Framework version: 0.23-1
Python version: 3.10
CPU or GPU: CPU
Custom Docker image (Y/N): N
It should also be noted that we are experiencing this issue with custom algorithms deployed as ECR images.
Additional context
This is the same issue as the unresolved bug from 2023 which is already closed
https://github.com/aws/sagemaker-python-sdk/issues/4120
贡献指南
调研方向
报告的入口点是 ModelPackage.from_model_package_arn、ModelCard(...)、mc.create() 和 aws sagemaker list-model-cards;将已创建模型卡的字段与 Model Cards UI 列出的字段进行比较。查看 issue #4120,并在 Governance → Model cards 中验证结果;完成的标准是,根据模型包详细信息创建的卡片会显示在那里。
由索引模型根据 Issue 内容生成。
评估
- 技术栈
- aws, machine-learning, python
- 领域
- cloud, machine-learning
- Issue 类型
- 缺陷
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 活跃度
- 停滞
- 描述清晰度
- 基本清楚
- 新手友好度
- 35/100