aws / aws/sagemaker-python-sdk
ModelStep should have a 'adds_depends_on' class method
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- Python
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描述
**Describe the feature you'd like**
When constructing SageMaker pipelines, I want to construct steps that sequence Training jobs (TrainingStep) and Inference jobs (ModelStep and TransformStep) together. As part of this, I would use `add_depends_on` from the TrainingStep to allow me to string together tasks. However, we cannot do the same for ModelStep. It has to be passed via the `depends_on` parameter during initialization.
**How would this feature be used? Please describe.**
```
def setup(…):
model_step = ModelStep(…)
transform_step = TransformStep(…, model_step…)
model_step.add_depends_on(other_steps)
```
**Describe alternatives you've considered**
I am forced to pass in dependencies throughout my abstractions, rather than construct the model_step first, and then add dependencies later.
**Additional context**
happy to add more details if needed.
贡献指南
调研方向
首先定位 issue 中提到的 ModelStep、TrainingStep 和 TransformStep 入口点,然后比较 TrainingStep 如何处理 add_depends_on 与 ModelStep 的 depends_on 初始化参数。通过构建所示的 pipeline 序列并检查生成的依赖关系是否得到保留,确认所请求的用法。
由索引模型根据 Issue 内容生成。
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- 技术栈
- aws, python
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- machine-learning
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- 3/5
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- 1-2 天
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