Generate all hyperparameter combinations
Quick Overview
This question evaluates competence in combinatorial enumeration and manipulation of data structures for generating hyperparameter configurations, testing understanding of Cartesian products and correctness of produced configuration sets.
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Jan 22, 2026, 12:00 AM
Machine Learning Engineer
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Coding & Algorithms
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You are given several groups of hyperparameter choices for an ML experiment. Each group contains one hyperparameter name and a list of candidate values.
Return all possible configurations (the Cartesian product across groups), where each configuration assigns exactly one value to each hyperparameter.
Input
-
A list of
khyperparameter groups, e.g.-
[("lr", [0.1, 0.01]), ("batch", [16, 32, 64]), ("optimizer", ["sgd", "adam"])]
-
Output
- A list of configurations, each configuration represented as a map/dictionary from name → chosen value.
Constraints / expectations
- If any group has an empty value list, the result should be empty.
- Order does not matter, but the output should not contain duplicates.
- Discuss a few test cases (including edge cases) you would use to validate the implementation.