tensorflow / tensorflow/model-optimization

Tracking TFMOT 1.0.0 Release

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technique:all
Dominant language
Python
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Description

This issue tracks potential changes that would be made in a 1.0.0 release.
This should be quite far off at this point.

Pruning:

  • see how pruning the kernel in DepthwiseConv2D influences converging accuracy. If not significant, prune by default. (prune_registry.py)
  • use only tf.math.divide instead of tf.div for 1.XX (pruning_schedule.py > PolynomialDecay > call )

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Review prune_registry.py and pruning_schedule.py, especially PolynomialDecay.call, and determine which release changes are still required. The issue names no tests or acceptance criteria, so completion would require a concrete 1.0.0 scope and verification plan.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, tensorflow
Domain
machine-learning, release
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
15/100

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