piskvorky/gensim

Check what's the reason to use double-precision in topic models

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#1,576 opened on Sep 8, 2017

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Description

Our TMs return vectors with double-precision float64, it looks like very suspicious, because float32 is enough for all. Need to check, what's a reason of this behavior and what's a concrete method.

The first step - look at this line in the test, after it - collect all TMs, that depends on this tests and check, where and why float64 happened.

Result - detailed description (where and why), and fixing this behavior after discussion (if needed)

Contributor guide

Research direction
Inspect the test line at basetmtests.py#L51, then trace where and why float64 is used across all topic models that depend on that test. Document findings and propose a fix if appropriate.
Tech stack
python
Domain
machine learning
Issue type
Research
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
PythonGensim
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
65