[Feature] Add Tokens-to-Token ViT backbone and converted checkpoints. #467
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@@ Coverage Diff @@
## master #467 +/- ##
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+ Coverage 78.77% 79.42% +0.64%
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Files 103 106 +3
Lines 5702 5959 +257
Branches 927 962 +35
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+ Hits 4492 4733 +241
- Misses 1088 1095 +7
- Partials 122 131 +9
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Ezra-Yu
reviewed
Oct 28, 2021
| assert out_indices[i] >= 0, f'Invalid out_indices {index}' | ||
| self.out_indices = out_indices | ||
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| dpr = [x for x in np.linspace(0, drop_path_rate, num_layers)] |
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dpr could be "droppath rates" or "drop rates".
it is better to use droppath_rates.
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Right, but dpr is used in VisionTransformer and SwinTransformer, and it's a conventional usage.
mzr1996
added a commit
to mzr1996/mmpretrain
that referenced
this pull request
Nov 24, 2022
…open-mmlab#467) * add t2t backbone * register t2t_vit * add t2t_vit config * [Temp] Align posterize transform with timm. * Fix lint * Refactor t2t-vit * Add config for t2t-vit * Add metafile and README for t2t-vit * Add unit tests * configs * Update metafile and README * Improve docstring * Fix batch size which should be 8x64 instead of 8x128 * Fix typo * Update model zoo * Update training augments config. * Move some arguments of T2TModule to T2TViT * Update docs. * Update unit test Co-authored-by: HIT-cwh <[email protected]>
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Motivation
Continue @HIT-cwh's work
Modification
As the title.
This PR depends on #395, please review that PR at first.
BC-breaking (Optional)
No.
Use cases (Optional)
No.
Checklist
Before PR:
After PR: