aws / aws/sagemaker-python-sdk
[Feature request]: Selectively execute a pipeline step which has upstream dependencies
- 主要言語
- Python
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説明
**Describe the feature you'd like**
A feature to selectively execute a sagemaker pipeline step which has upstream dependencies when all the dependent parameter for the step is passed via a dict.
Presently using `sagemaker.workflow.selective_execution_config.SelectiveExecutionConfig` to execute a pipeline with dependencies gives a client error.
```sh
ClientError: An error occurred (ValidationException) when calling the StartPipelineExecution operation: Invalid
SourcePipelineExecutionArn: null. The selected steps [] have dependencies on [, ...]
```
The expected behavior would be to execute the step successfully when the dependent parameters are passed.
**How would this feature be used? Please describe.**
- Selective execution of steps which are downstream which have many dependencies. Executing all the dependencies seems wasteful.
**Describe alternatives you've considered**
- Execute all dependencies, current feature.
- Create a temporary new pipeline with the specification for the step by removing the dependency and executing it.
**Additional context**
sagemaker sdk version: 2.208.0
Any alternative or suggestion would be helpful.
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