[MADLIB-1375] ParamSearch: Add utility function for generating model selection table

• Type: New Feature
• Status: Closed
• Priority: Major
• Resolution: Fixed
• Fix Version/s: v1.17
• Component/s: Deep Learning
• Assignee: Unassigned
• Reporter: Yuhao Zhang
• Created: 08/Aug/19 17:17
• Updated: 03/Sep/19 16:42
• Resolved: 03/Sep/19 16:42

Description

As part of this JIRA, we create a utility function to generate the model selection table.
The user, inputs the model_arch_table, sets of model_arch_ids, compile_params, and fit_params. The utility function creates a table with a combination of these three inputs, each with a distinct `MST_KEY`.

API

load_model_selection_table(
model_arch_table, 
model_selection_table, -- output table name
ARRAY[] model_arch_id, -- Assuming there is only 1 model_arch_table and all model_arch_id are from that table
ARRAY[] compile_params,
ARRAY[] fit_params
)

*Output Model Selection Table
*

MST_Key (sequence)	model_arch	model_arch_id	compile_params	fit_params
1	model_arch_library	1	C1	F1
2	model_arch_library	2	C2	F2
3	model_arch_library	3	C3	F3

Acceptance
1. Validate model_arch_table exists and model_selection_table does not exist
2. The utility function should error if the user inputs an invalid model_arch_id
3. The utility function should error if user inputs invalid compile_param/fit_param
4. The utility function should deduplicate model_arch_id, compile_param, fit_param if passed in

*Notes/open questions
1. We may want to offer other options later for automatically generating the `model_selection_table` (e.g., log, random)
2. How to reconcile with Keras and other libraries that have param selection capability? We are working at a higher level here, but can we take advantage nonetheless?