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To run a pipeline, you point the run CLI at a file with a get_config function that returns an instance of PipelineConfig. This is useful for storing particular configurations especially when they are very complex, but seems unnecessarily convoluted if you just want to run a pipeline using all the default options and a few overrides of those defaults. An alternative would be the ability to just point the run CLI at a PipelineConfig class, and supply any fields and their values to override. Example invocation: rastervision2 run my_module.MyPipelineConfig --override x 3 --override a.b "hello" This would make sense for pipelines that do some ephemeral data processing that was perhaps kicked off in an automated way by some other process.
Some things to think about:
How to represent overrides of nested or array fields
How to do input validation (can we harness the builtin Pydantic validation as much as possible)
Generating useful --help docs that list the fields in an automated way from the Pydantic field descriptions
The text was updated successfully, but these errors were encountered:
To run a pipeline, you point the
run
CLI at a file with aget_config
function that returns an instance ofPipelineConfig
. This is useful for storing particular configurations especially when they are very complex, but seems unnecessarily convoluted if you just want to run a pipeline using all the default options and a few overrides of those defaults. An alternative would be the ability to just point therun
CLI at aPipelineConfig
class, and supply any fields and their values to override. Example invocation:rastervision2 run my_module.MyPipelineConfig --override x 3 --override a.b "hello"
This would make sense for pipelines that do some ephemeral data processing that was perhaps kicked off in an automated way by some other process.Some things to think about:
--help
docs that list the fields in an automated way from the Pydantic field descriptionsThe text was updated successfully, but these errors were encountered: