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There are a lot of parameters needed for the ilab pipeline, and they are each individually relevant to the SDG, Training or Eval steps. However, the parameter names provide no hint to the users as to what part of the pipeline they control. Furthermore, DSP automatically displays them in alphabetical order. This is simply confusing and not a good user experience. See image below for an example.
We should rename all the params with an appropriate prefix (sdg_, train_, eval_mtbench_, and eval_final_) so that they will be group logically on the "Create Run" page.
The text was updated successfully, but these errors were encountered:
@dsl.pipeline(display_name='Test pipeline')defpipeline(
sdg_foo: str,
train_baz: str,
):
"""This is a test pipeline. Args: sdg_foo: This is an SDG parameter Foo that does Bar. train_baz: This is a Training parameter Baz that does Qux. """
...
Which translates to IR YAML:
pipelineInfo:
description: This is a test pipeline.
displayName: Test pipeline
name: pipeline
root:
dag:
...
inputDefinitions:
parameters:
sdg_foo:
description: This is an SDG parameter Foo that does Bar.
parameterType: STRING
train_baz:
description: This is a Training parameter Baz that does Qux.
parameterType: STRING
There are a lot of parameters needed for the ilab pipeline, and they are each individually relevant to the SDG, Training or Eval steps. However, the parameter names provide no hint to the users as to what part of the pipeline they control. Furthermore, DSP automatically displays them in alphabetical order. This is simply confusing and not a good user experience. See image below for an example.
We should rename all the params with an appropriate prefix (
sdg_
,train_
,eval_mtbench_
, andeval_final_
) so that they will be group logically on the "Create Run" page.The text was updated successfully, but these errors were encountered: