model: pytorch: pretrained: Add support for additional layers Python API

[mhash1m]

fixes: #1147

• This PR is a dependency for the usecase example notebook I'm currently working on, ie. "Transferlearning".

• I ended up setting layers: Anyin the PyTorchPreTrainedModelConfig and also skipping convert_value() in base.py if field type is Any since it tries to create an instance of the type.

• Seems to be working as I handle the formatting of the parameter in pytorch_pretrained itself, but what could be the implications of this?

• It appears we don't have Any type fields, even if we add in future and want to by-pass the checks in base.py, we can simply provide multiple arguments to isinstance() to check against along with dict, to allow the convert_value() process.

• Alternatively, I could also create a .yaml inside the notebook (for the time being) if this approach doesn't seem right.

• Using Pillow==8.2.0 to temporarily fix the pytorch errors. Seems like there's a pending fix Make Image.__array__ take optional dtype argument python-pillow/Pillow#5572 so should be okay soon

[codecov-commenter]

Codecov Report

Merging #1148 (9da27e9) into master (5edb093) will decrease coverage by 0.03%.
The diff coverage is 0.00%.

@@            Coverage Diff             @@
##           master    #1148      +/-   ##
==========================================
- Coverage   84.63%   84.60%   -0.04%     
==========================================
  Files         156      156              
  Lines       10180    10184       +4     
  Branches     1677     1679       +2     
==========================================
  Hits         8616     8616              
- Misses       1215     1218       +3     
- Partials      349      350       +1     

Impacted Files	Coverage Δ
dffml/base.py	83.60% <0.00%> (-1.12%)	⬇️

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[pdxjohnny]

Pinging @sakshamarora1 and or @yashlamba for review

[pdxjohnny]

• Add releated PR number to commit message trailer