aws / aws/sagemaker-python-sdk
SageMaker Model Cards UI doesn't show Model Cards created using model package details
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Descripción
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
Guía de contribución
Línea de trabajo
Los puntos de entrada indicados son ModelPackage.from_model_package_arn, ModelCard(...), mc.create() y aws sagemaker list-model-cards; compara los campos de la tarjeta de modelo creada con los campos que muestra la Model Cards UI. Revisa el issue #4120 y verifica el resultado en Governance → Model cards; se considera terminado cuando las tarjetas creadas a partir de los detalles del paquete de modelos aparecen allí.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- aws, machine-learning, python
- Área
- cloud, machine-learning
- Tipo de issue
- Error
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Estado de actividad
- Estancado
- Claridad
- Bastante claro
- Aptitud para principiantes
- 35/100