[Docs] Add code-spell pre-commit hook and fix a large mount of typos.

[mzr1996]

Motivation

Refers to open-mmlab/mmdetection#6099, this hook can check all typos in the code, it can help us to avoid typos.

Modification

As the title.

BC-breaking (Optional)

It may break CI if new PRs have typos.

Use cases (Optional)

No, just a pre-commit hook.

Checklist

Before PR:

• Pre-commit or other linting tools are used to fix the potential lint issues.
• Bug fixes are fully covered by unit tests, the case that causes the bug should be added in the unit tests.
• The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
• The documentation has been modified accordingly, like docstring or example tutorials.

After PR:

• If the modification has potential influence on downstream or other related projects, this PR should be tested with those projects, like MMDet or MMSeg.
• CLA has been signed and all committers have signed the CLA in this PR.

[Ezra-Yu]

LGTM.

[codecov]

Codecov Report

Merging #470 (53df664) into master (6fba107) will decrease coverage by 0.04%.
The diff coverage is 42.70%.

@@            Coverage Diff             @@
##           master     #470      +/-   ##
==========================================
- Coverage   78.01%   77.97%   -0.05%     
==========================================
  Files         101      102       +1     
  Lines        5617     5620       +3     
  Branches      923      923              
==========================================
  Hits         4382     4382              
- Misses       1108     1111       +3     
  Partials      127      127              

Flag	Coverage Δ
unittests	77.97% <42.70%> (-0.05%)	⬇️

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

Impacted Files	Coverage Δ
mmcls/core/visualization/image.py	89.07% <ø> (ø)
mmcls/datasets/pipelines/formating.py	0.00% <0.00%> (-43.48%)	⬇️
mmcls/datasets/pipelines/transforms.py	86.81% <ø> (ø)
mmcls/models/backbones/mobilenet_v3.py	100.00% <ø> (ø)
mmcls/models/backbones/regnet.py	98.03% <ø> (ø)
mmcls/models/backbones/repvgg.py	96.84% <ø> (ø)
mmcls/models/backbones/tnt.py	99.08% <ø> (ø)
mmcls/models/backbones/vgg.py	86.58% <ø> (ø)
mmcls/models/backbones/vision_transformer.py	77.54% <ø> (ø)
mmcls/models/classifiers/base.py	69.62% <ø> (ø)
... and 8 more

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[Ezra-Yu]

LGTM.