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[Enhance] Infer batch_size using len(result) to support MMDet3D #532

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merged 1 commit into from
May 6, 2021
Merged

[Enhance] Infer batch_size using len(result) to support MMDet3D #532

merged 1 commit into from
May 6, 2021

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Wuziyi616
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MMDet3D data doesn't have 'img' term. Instead, we infer batch_size from len(result). MMDet also adopts this fashion here.

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codecov bot commented May 6, 2021

Codecov Report

Merging #532 (1b36d02) into master (aa9b609) will not change coverage.
The diff coverage is 0.00%.

❗ Current head 1b36d02 differs from pull request most recent head f60de7a. Consider uploading reports for the commit f60de7a to get more accurate results
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@@           Coverage Diff           @@
##           master     #532   +/-   ##
=======================================
  Coverage   86.79%   86.79%           
=======================================
  Files         101      101           
  Lines        5249     5249           
  Branches      848      848           
=======================================
  Hits         4556     4556           
  Misses        533      533           
  Partials      160      160           
Flag Coverage Δ
unittests 86.79% <0.00%> (ø)

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Impacted Files Coverage Δ
mmseg/apis/test.py 22.68% <0.00%> (ø)

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@xvjiarui xvjiarui merged commit db44d16 into open-mmlab:master May 6, 2021
@Wuziyi616 Wuziyi616 deleted the mmdet3d_compatibility branch July 14, 2021 09:04
bowenroom pushed a commit to bowenroom/mmsegmentation that referenced this pull request Feb 25, 2022
aravind-h-v pushed a commit to aravind-h-v/mmsegmentation that referenced this pull request Mar 27, 2023
…#532)

* 2x speedup using memory efficient attention

* remove einops dependency

* Swap K, M in op instantiation

* Simplify code, remove unnecessary maybe_init call and function, remove unused self.scale parameter

* make xformers a soft dependency

* remove one-liner functions

* change one letter variable to appropriate names

* Remove Env variable dependency, remove MemoryEfficientCrossAttention class and use enable_xformers_memory_efficient_attention method

* Add memory efficient attention toggle to img2img and inpaint pipelines

* Clearer management of xformers' availability

* update optimizations markdown to add info about memory efficient attention

* add benchmarks for TITAN RTX

* More detailed explanation of how the mem eff benchmark were ran

* Removing autocast from optimization markdown

* import_utils: import torch only if is available

Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>
wjkim81 pushed a commit to wjkim81/mmsegmentation that referenced this pull request Dec 3, 2023
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2 participants