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EPIC: Refactor pip package #493

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9 of 10 tasks
MalteEbner opened this issue Sep 15, 2021 · 3 comments
Open
9 of 10 tasks

EPIC: Refactor pip package #493

MalteEbner opened this issue Sep 15, 2021 · 3 comments
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@MalteEbner
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MalteEbner commented Sep 15, 2021

Current state:

Currently, we offer 3 levels of SSL parts:

Target state:

We remove the mid-level representations (delete that code). We provide more examples on the high-level: One example pytorch lightning module for every implemented paper

Steps towards it

Always merge into the development branch: https://github.com/lightly-ai/lightly/tree/master-refactor-SSL-models

First step:

Second step:

Third step:

  • delete mid-level models in lightly/lightly/models
@MalteEbner
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MalteEbner commented Sep 20, 2021

What is still unclear for me is which versions will belong to which steps. We should have clear plans when what will deprecate. In particular, we need published python versions where deprecations warning are raised, but the old models still work.

E.g:

  • versions with 1.1.xxxx: Old models work without deprecations warnings. This is the state before this issue.
  • versions with 1.2.xxxx: New models are working. Old models are still there and working, but raise deprecation warnings. This equals step 1 of this EPIC. We should use the branch master-refactor-SSL-models for it.
  • versions with 1.3.xxxx The old models are removed. This equals step 2 of the epic. We should use a new branch for it.

@philippmwirth
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philippmwirth commented Nov 18, 2021

Requirements for 1.2.0, goal: mid-level models are removed

  • Documentation and tutorials are up-to-date (no mid-level models are used)
    • one issue per tutorial
    • one issue for rest of docs
  • Ensure CLI tool works (doesn't use mid-level models)
  • Remove mid-level models
  • Refactor loss function (make symnegcosine non-symmetrical)

@guarin
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guarin commented Nov 24, 2021

The cli still uses SelfSupervisedEmbedding objects. We should decide whether we want to continue using it or also change to low level.

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