UPI Interface Update #6
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added 18 commits
September 2, 2022 16:41
…ediction-interface into proto_update
added 7 commits
September 6, 2022 10:25
…erface into proto_update
…erface into proto_update
MJeremy2017
reviewed
Sep 6, 2022
| // Each table doesn't need to have same number of row. | ||
| repeated Table tables = 1; | ||
| // List of variables | ||
| repeated NamedValue variables = 2; |
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do you see concrete use cases for variables? Might it be simpler to make everything a table?
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I think there are valid cases to declare scalar variable based on current usage of standard transformer.
Might it be simpler to make everything a table?
It is simpler but by not much.
leonlnj
approved these changes
Sep 12, 2022
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Motivated by the need for more flexible data passing mechanism and more efficient interface definition for large message we introduces following changes in this PR:
Introduction of
Tabledata structureTable represents dataframe-like data structure in row-based format. Table has following specifications:
row_id(similar purpose torow_idin the PredictionRow)Replace
prediction_rowsin the request andprediction_result_rowsin the response to useTabledefinitionprediction_rowsandprediction_result_rowsare technically a dataframe-like object which can be represented as aTableDeserialization performance is improved significantly by at least 2x for various message size.
NOTE:
0001_7467c7bis the existing interface whereas0002_ac3775cis with the changes.Serialization performance is also improved, although not as significant as the deserialization perforamance.
Move
transformer_inputsas top level field in the requestThis PR extracts
transformer_inputsfrom withinprediction_rowsto top level request field to improve flexibility of passing data from client without having to denormalize it beforehand. A new proto messageTransformerInputis introduced to store all tables and variables that need to be passed to standard transformer.Add utility package
2 utility functions are added to the package to facilitate a more user-friendly api to use
Table:df_to_table--> to convert pandas DataFrame to Tabletable_to_df--> to convert Table into pandas DataFrameExample usage is as follow:
Note
The PR contains generated docs and code, thus it's better to start the review with following source files: