the-algorithm-ml

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Darshan P ca8db6ddf4 Refactored rank-specific logger

#Refactored rank_specific functions.
#Implemented the logic without changing the behavior.
#The readability and maintainability of the code improved.
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Tested against:
test_torch_logging.py

2023-04-02 18:19:39 +00:00

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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common

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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core

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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ml_logging

Refactored rank-specific logger

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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.pre-commit-config.yaml

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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COPYING

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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LICENSE.torchrec

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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model.py

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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pyproject.toml

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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README.md

Twitter's Recommendation Algorithm - Heavy Ranker and TwHIN embeddings

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README.md

This project open sources some of the ML models used at Twitter.

Currently these are:

The "For You" Heavy Ranker (projects/home/recap).
TwHIN embeddings (projects/twhin) https://arxiv.org/abs/2202.05387

This project can be run inside a python virtualenv. We have only tried this on Linux machines and because we use torchrec it works best with an Nvidia GPU. To setup run

./images/init_venv.sh (Linux only).

The READMEs of each project contain instructions about how to run each project.