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add loggings for internal adoption tracking #426

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pikapecan
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Summary:
add adoption loggings for models with most internal usage. To avoid duplicated count, we only enable loggings for model entrypoints.
This diff includes: vision transformer, MLP, av_concat_fusion, contrastive loss and transformer fusion. CLIP logging has been enabled previously.

Reviewed By: ankitade

Differential Revision: D45532797

Summary:
add adoption loggings for models with most internal usage. To avoid duplicated count, we only enable loggings for model entrypoints.
This diff includes: vision transformer, MLP, av_concat_fusion, contrastive loss and transformer fusion. CLIP logging has been enabled previously.

Reviewed By: ankitade

Differential Revision: D45532797

fbshipit-source-id: d0241119fc89b7bce1e151697fbcceda624ca792
@facebook-github-bot facebook-github-bot added CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. fb-exported labels May 4, 2023
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This pull request was exported from Phabricator. Differential Revision: D45532797

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codecov-commenter commented May 4, 2023

Codecov Report

Patch coverage: 100.00% and no project coverage change.

Comparison is base (f51c16b) 64.56% compared to head (6fbbc3f) 64.57%.

Additional details and impacted files
@@           Coverage Diff           @@
##             main     #426   +/-   ##
=======================================
  Coverage   64.56%   64.57%           
=======================================
  Files         146      146           
  Lines        9836     9838    +2     
=======================================
+ Hits         6351     6353    +2     
  Misses       3485     3485           
Impacted Files Coverage Δ
torchmultimodal/modules/layers/mlp.py 100.00% <100.00%> (ø)
...odules/losses/contrastive_loss_with_temperature.py 90.56% <100.00%> (+0.18%) ⬆️

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This pull request has been merged in b5981a4.

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3 participants