[Docs] cnn.md translated

[bofen97]

Motivation

Document translation

Modification

Modified: docs_zh_CN/understand_mmcv/cnn.md

BC-breaking (Optional)

None

Use cases (Optional)

None

[zhouzaida]

hi bofen97, thanks for your contribution. Please resolve above comments and we will merge the PR in the next version

[codecov]

Codecov Report

Merging #1246 (16962a1) into master (04daea4) will increase coverage by 0.87%.
The diff coverage is 92.98%.

❗ Current head 16962a1 differs from pull request most recent head ed888e3. Consider uploading reports for the commit ed888e3 to get more accurate results

@@            Coverage Diff             @@
##           master    #1246      +/-   ##
==========================================
+ Coverage   68.27%   69.14%   +0.87%     
==========================================
  Files         160      162       +2     
  Lines       10599    10746     +147     
  Branches     1937     1978      +41     
==========================================
+ Hits         7236     7430     +194     
+ Misses       2979     2927      -52     
- Partials      384      389       +5     

Flag	Coverage Δ
unittests	69.14% <92.98%> (+0.87%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
mmcv/__init__.py	100.00% <ø> (ø)
mmcv/arraymisc/__init__.py	100.00% <ø> (ø)
mmcv/arraymisc/quantization.py	100.00% <ø> (ø)
mmcv/cnn/__init__.py	100.00% <ø> (ø)
mmcv/cnn/alexnet.py	26.08% <ø> (ø)
mmcv/cnn/bricks/__init__.py	100.00% <ø> (ø)
mmcv/cnn/bricks/activation.py	87.50% <ø> (ø)
mmcv/cnn/bricks/context_block.py	96.96% <ø> (ø)
mmcv/cnn/bricks/conv.py	100.00% <ø> (ø)
mmcv/cnn/bricks/conv2d_adaptive_padding.py	94.73% <ø> (ø)
... and 103 more

---

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 04daea4...ed888e3. Read the comment docs.

[OpenMMLab-Coodinator]

Hi @bofen97 ！First of all, we want to express our gratitude for your significant PR in this project. Your contribution is highly appreciated, and we are grateful for your efforts in helping improve this open-source project during your personal time. We believe that many developers will benefit from your PR.

We would also like to invite you to join our Special Interest Group (SIG) private channel on Discord, where you can share your experiences, ideas, and build connections with like-minded peers. To join the SIG channel, simply message moderator— OpenMMLab on Discord or briefly share your open-source contributions in the #introductions channel and we will assist you. Look forward to seeing you there! Join us ：https://discord.gg/UjgXkPWNqA

If you have WeChat account，welcome to join our community on WeChat. You can add our assistant ：openmmlabwx. Please add "mmsig + Github ID" as a remark when adding friends：）
Thank you again for your contribution❤