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Have the various nested components pass metadata up out of them, and have orchestrate_pipeline() handle saving the metadata.
Context
Metadata is currently saved by write_outputs(), which means passing information down into it and model_logic() about blob storage, which they don't need to know about.
Requirements
Ideally, the metadata would be returned from execute_model_logic() as a value, and orchestrate_pipeline() would be the function that writes the values to disk. Starting at the most nested function first:
write_model_outputs() does not write the metadata. Alter it to return the samples_path, summaries_path, and model_path it used when writing the samples, summaries, and model.
Alter the tests that check the return value and metadata saving.
execute_model_logic() accepts the returned paths from write_model_outputs(), and adds them to the metadata list. It then returns the metadata list. Also add model completion status to the metadata?
Alter the tests that check the return value.
orchestrate_pipeline() accepts the metadata list from execute_model_logic(). It adds the blob storage container to the metadata. It writes the metadata to file, using the dirname() of the model path.
Alter tests that check the output of orchestrate_pipeline(). Add tests for checking that metadata has been saved to disk.
Out of scope
Anything that isn't about setting up better handling of the metadata.
Goal
Have the various nested components pass metadata up out of them, and have
orchestrate_pipeline()
handle saving the metadata.Context
Metadata is currently saved by
write_outputs()
, which means passing information down into it andmodel_logic()
about blob storage, which they don't need to know about.Requirements
Ideally, the metadata would be returned from
execute_model_logic()
as a value, andorchestrate_pipeline()
would be the function that writes the values to disk. Starting at the most nested function first:write_model_outputs()
does not write the metadata. Alter it to return thesamples_path
,summaries_path
, andmodel_path
it used when writing the samples, summaries, and model.execute_model_logic()
accepts the returned paths fromwrite_model_outputs()
, and adds them to themetadata
list. It then returns the metadata list. Also add model completion status to the metadata?orchestrate_pipeline()
accepts the metadata list fromexecute_model_logic()
. It adds the blob storage container to the metadata. It writes the metadata to file, using thedirname()
of the model path.orchestrate_pipeline()
. Add tests for checking that metadata has been saved to disk.Out of scope
Related
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