[PyTorch][references] fix pretrained with different vocabs

[felixdittrich92]

This PR fixes the mismatching linear layers at each model if we pass a different vocab as french and the pretrained flag to the training scripts

• recognition: only crnn because sar and master broken and have currently no pretrained version
• classification: all

Any feedback is welcome 🤗

[codecov]

Codecov Report

Merging #874 (0bbbb94) into main (509fce8) will decrease coverage by 0.00%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #874      +/-   ##
==========================================
- Coverage   94.84%   94.84%   -0.01%     
==========================================
  Files         133      133              
  Lines        5200     5215      +15     
==========================================
+ Hits         4932     4946      +14     
- Misses        268      269       +1     

Flag	Coverage Δ
unittests	94.84% <100.00%> (-0.01%)	⬇️

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

Impacted Files	Coverage Δ
doctr/models/classification/magc_resnet/pytorch.py	100.00% <100.00%> (ø)
doctr/models/classification/mobilenet/pytorch.py	100.00% <100.00%> (ø)
doctr/models/classification/resnet/pytorch.py	100.00% <100.00%> (ø)
doctr/models/classification/vgg/pytorch.py	100.00% <100.00%> (ø)
doctr/models/recognition/crnn/pytorch.py	94.38% <100.00%> (+0.12%)	⬆️
doctr/models/utils/pytorch.py	100.00% <100.00%> (ø)
doctr/transforms/functional/base.py	95.65% <0.00%> (-1.45%)	⬇️
doctr/transforms/modules/base.py	94.59% <0.00%> (ø)

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[charlesmindee]

Thank you for the fix!

[felixdittrich92]

@charlesmindee TF needs the same but will do in another PR :) i think in TF its enough to modify the checkpoint loading